Targeted Parasite Elimination in the Human and Mosquito to Reduce Malaria Transmission: A Cluster Randomised Controlled Factorial Design Trial of Reactive Focal Drug Administration (rfMDA) Versus Reactive Case Detection (RACD), With and Without Reactive Vector Control (RAVC), From the Low Endemic Setting of Namibia
Phase: PHASE3
Conditions: Malaria
Sponsor: University of California, San Francisco

1 
 
 
 
Evaluating the feasibility of reactive focal mass drug administration vs. reactive case 
detection, with and without reactive vector control, as a community level intervention in 
response to confirmed, passively identified index cases in Zambezi region, Namibia 
Phase II of a two-phase study 
 
 
 
 
Principal Investigators: Davis Mumbengegwi1, Michelle Hsiang2,3, Roly Gosling2, Jennifer Smith2, 
Adam Bennett2, and Immo Kleinschmidt4,6 
Co-investigators: Petrina Uusiku5, Stark Katokele5, Ronnie Bock1, Kathryn Roberts2, Lisa Prach2, 
Oliver Medzihradsky2, and Bryan Greenhouse2 
 
Funders 
The Novartis Foundation 
The Bill & Melinda Gates Foundation 
Horchow Family Fund  
 
 
Contributing Partners 
1 Multidisciplinary Research Centre, University of Namibia 
2 Malaria Elimination Initiative, Global Health Group, University of California, San Francisco 
3 Department of Pediatrics, University of Texas Southwestern Medical Center 
4 London School of Hygiene and Tropical Medicine 
5 Namibia Ministry of Health and Social Services 
6 School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 
 
 
 
 
 
Version Number: 1.9 
Aug 25, 2018 
 
 
 
 
 
 
 

Reactive Targeted Parasite Elimination to Reduce Malaria in Zambezi Region, Namibia 
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Table of Contents 
Abbreviations and Acronyms ...............................................................................................................................3 
Definitions ...........................................................................................................................................................4 
Study Summary ....................................................................................................................................................6 
Key Personnel ....................................................................................................................................................10 
Partners and qualifications ................................................................................................................................13 
1.0 
Background ...........................................................................................................................................15 
2.0 
Rationale ...............................................................................................................................................19 
3.0 
Study Aims ............................................................................................................................................21 
4.0 
Study Site ..............................................................................................................................................21 
5.0 
Study design .........................................................................................................................................22 
6.0 
Study procedures ..................................................................................................................................25 
7.0 
Safety and Risks ....................................................................................................................................33 
8.0 
Laboratory procedures .........................................................................................................................36 
9.0 
Entomological management .................................................................................................................38 
10.0 
Data management ................................................................................................................................38 
11.0 
Statistical considerations ......................................................................................................................39 
11.7 
Analysis .................................................................................................................................................42 
12.0 Ethics considerations .................................................................................................................................45 
13.0 Timeline .....................................................................................................................................................50 
14.0 References .................................................................................................................................................51 
15.0 Appendices ................................................................................................................................................53 
 
 
 
 
 
 
 

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Abbreviations and Acronyms 
ACT 
Artemisinin-based combination therapy 
AL 
Artemether-lumefantrine 
CHAI  
Clinton Health Access Initiative 
DBS  
Dried blood spot 
DOT 
Directly observed therapy 
DP 
Dihydroartemisinin-piperaquine 
DSMB 
Data Safety and Monitoring Board 
EA 
Enumeration Area 
ELISA  
Enzyme-linked immunoabsorbent assay 
 
GIS 
Geographic information system 
GPS 
Global positioning system 
HH 
Household 
HRP II 
Histidine-rich protein II 
HS RDT  
Highly sensitive rapid diagnostic test 
IRB 
Institutional Review Board 
IRS  
Indoor residual spraying 
ITN  
Insecticide treated net 
ITT 
Intention to treat 
LAMP  
Loop-mediated isothermal amplification 
LLIN 
Long-lasting insecticide treated bed net  
LSHTM  
London School of Hygiene and Tropical Medicine 
MoHSS  
Ministry of Health and Social Services 
MEI 
Malaria Elimination Initiative 
MRC  
Multidisciplinary Research Centre 
NVDCP  
National Vector-borne Diseases Control Programme 
PCR  
Polymerase chain reaction 
Pf 
Plasmodium falciparum 
PI 
Principal Investigator 
QTc 
Corrected QT interval 
RACD  
Reactive case detection 
RAVC 
Reactive vector control 
RDT  
Rapid diagnostic test 
rfMDA 
reactive focal mass drug administration 
SAE 
Severe adverse event 
SARN – RBM Southern African Regional Network of Roll Back Malaria 
SNP 
Single nucleotide polymorphism 
SOP 
Standard operating procedures 
SDSS  
Spatial decision support system 
SUSAR  
Suspected unexpected severe adverse reaction 
TPE  
Targeted parasite elimination 
UCSF  
University of California, San Francisco 
UNAM  
University of Namibia 
 
 
 

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Definitions  
Active surveillance: A strategy to detect and record cases of malaria within a community by 
conducting screening away from a health facility. 
Case investigation: After a patient is diagnosed with malaria at a health facility, the patient is 
interviewed about his/her symptoms, recent travel, ITN use, and household IRS coverage. 
Case, malaria: A person in whom, regardless of the presence or absence of clinical symptoms, malaria 
parasites have been confirmed by quality-controlled diagnosis. 
Case, imported: A person in whom the origin of malaria infection can be traced to a known malarious 
area outside the country in which the case was diagnosed, generally classified based on travel history. 
Case, local: A person in whom the origin of malaria infection cannot be traced to a known malarious 
area outside the country where the case was diagnosed, generally classified based on travel history and 
local epidemiology. 
Case, index: A person diagnosed with malaria via rapid diagnostic test (RDT) or microscopy, whose 
infection is included in the passive surveillance system; the trigger for reactive case detection. 
Coverage: The proportion of the targeted population reached by a given intervention. Also known as 
operational coverage. 
Hotspot: A location of geographically clustered malaria where transmission is more intense. 
Household: Any single or collection of permanent or semi-permanent dwelling structures acting as 
the primary residence for a person or group of people thatthat generally cook and eat together. Some 
households may include members who sleep in other dwelling structures within the same compound 
if the members are still dependent on the head of household in the main household. 
Household resident: Any person who usually resides within a household or slept in that household 
for at least one night in the past four weeks. 
Local epidemiology: The distribution and transmission of a disease within a defined area; the 
epidemiology of a disease can vary in different locations. 
Neighbour: A person living adjacent to the household of an index case. 
Passive surveillance: A system to detect and record malaria cases among patients who are diagnosed 
with malaria at health facilities. 
Reactive case detection: An active surveillance strategy where people living with or near an index 
case are screened and treated for malaria, and may be interviewed about their travel history, ITN use, 
household IRS coverage, and previous malaria-like illness. 
Reactive vector control: A response strategy where the household of an index case, as well as 
neighbouring households, receive IRS with a different insecticide after the index case is reported, 
regardless of whether spraying was already conducted pre-transmission; can be part of targeted parasite 
elimination. 
Severe adverse event: An experience that results in (1) death during the study period, (2) a life-
threatening experience (one that puts a participant at immediate risk of death at the time of the event), 
(3) inpatient hospitalization during the study period, (4) persistent or significant disability or 
incapacity, or (5) specific medical or surgical intervention to prevent one of the other serious outcomes 
listed above. 
Spatial decision support system: A geographical information system (GIS)-based system that 

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integrates a surveillance database, analytical models, graphical map display, tabular reporting, and 
expert knowledge. It provides a platform to support programmatic decision-making and spatially 
targeted approaches to disease control and elimination. 
Suspected unexpected severe adverse reaction: An adverse drug reaction that is suspected of having 
a causal relationship to the medication used in the research and is unexpected. 
Target area: The index case household and surrounding households closest to the index case. At least 
25 people should be enrolled in each target area, around each index case. The houses should be 
approached in order of their proximity to the index case household. Houses more than 500 m from the 
index case household should never be enrolled in the study. 
Targeted Parasite Elimination: A strategy to eliminate malaria parasites in people and mosquitoes 
in malaria “hotspots,” including administration of anti-malarial medication to communities with or 
without reactive targeted IRS. 
 

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Study Summary 
Title 
Evaluating the effectiveness and feasibility of reactive focal mass drug 
administration (rfMDA) vs. reactive case detection (RACD), with and without 
reactive vector control (RAVC), as a community level intervention in 
response to confirmed, passively identified malaria index cases in Zambezi 
region, Namibia 
Primary 
hypothesis 
We hypothesise that cumulative incidence will be lower in areas that receive 
RfMDA versus RACD and in areas that receive RAVC versus no RAVC. 
Study 
design 
Cluster randomised controlled trial with a 2x2 factorial design. 
Aims 
Primary aim: To compare the impact of RfMDA versus RACD, and RAVC 
versus no RAVC, on incidence of confirmed, passively identified malaria 
cases. 
Secondary aims 
Effectiveness: 
 
1) To compare the impact of each intervention package (RfMDA+/- RAVC, 
RACD +/-RAVC) on: 
a) Incidence, passively detected at health facilities 
b) Prevalence of infection, among all ages, as detected by LAMP 
c) Seroprevalence, among all ages, measured by ELISA 
 
Feasibility: 
1. To compare operational coverage, and determine the feasibility of 
reaching 80% coverage, for each intervention package; 
2. To compare safety of the intervention packages; 
3. To compare the acceptability of the interventions, individually and as 
packages; 
4. To compare the costs and cost-effectiveness of the interventions, 
individually and as packages; 
5. To measure medication adherence in both RfMDA and RACD arms. 
Study site 
Western Zambezi region, Namibia, a pre-elimination malaria setting. Eleven 
health facilities and their catchment areas will be included. The population of 
the study site is approximately 35,381 people. The study intervention will 
take place in a subset of Enumeration Areas, or EAs (see below “Sample 
size”). Additional samples may be obtained from confirmed cases passively 
detected at health facilities outside of this region, to better characterize 
parasite genotypes as local versus imported. 
Time frame 
October 2015 – December 2017 
Unit of 
randomisation 
Enumeration areas (EAs) within catchment areas of 11 study health facilities 
will be randomized to one of four intervention arms: 
1. RACD only              2.RACD with RAVC 
3.    RfMDA only                 4.RfMDA with RAVC 
Target area 
The index case household and additional houses closest to the index case, 
within 500m. 

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RfMDA and RACD: After the index case household, additional households 
will be enrolled, in order of distance from the index case, until at least 25 people 
have been enrolled. All households enrolled must be located within 500m of 
the index case household. If less than 25 people live within 500m of the index 
case, all those present and consenting will be enrolled. 
RAVC: The index case and six additional households will receive RAVC. 
Households will be approached in order of distance from the index case 
household. If any household is not home or refuses spraying, additional 
households will be approached to ensure seven total households, or all 
households within 500m of the index case household, receive RAVC. 
Intervention 
Each time a confirmed malaria case is detected by the passive surveillance 
system, it will be reported through a rapid reporting system and mapped. If that 
case is within a study EA a team including a nurse, a field investigator, and a 
driver will respond to the case. When appropriate an RAVC team will be 
dispatched to provide indoor residual spraying. The four intervention packages 
include: 
1. RACD only – Testing people in the index case household and closest 
neighbors who consent using RDTs, treating everyone who tests positive; 
2. RACD with RAVC – Testing people in the index case household and 
closest neighbors who consent using RDTs, treating everyone who tests 
positive, providing indoor residual spraying to index case and six closest 
consenting households within the Target Area; 
3. RfMDA only – Treating people in the index case household and closest 
neighbors who consent; 
4. RfMDA with RAVC – Treating people in the index case household and 
closest neighbours who consent, providing indoor residual spraying to 
index case and six closest consenting households within the Target Area. 
Treatment 
All index cases passively detected at health facilities, all subjects with a positive 
RDT, and all consenting residents of the RfMDA Target Area, will be treated 
with artemether lumefantrine (AL), in accordance with the first line malaria 
treatment in the MoHSS formulary. Those diagnosed with malaria by RDT will 
also be treated with a single low dose of primaquine, according to the malaria 
treatment guidelines of the MoHSS. 
Indoor 
residual 
spraying 
(IRS) 
The study area will receive pre-transmission season indoor residual spraying 
(IRS) as implemented by Ministry of Health and Social Services (MoHSS), 
where IRS and LLIN distribution are targeted rather than universal. In the 
study, when a new index case occurs in an enumeration area assigned to RAVC, 
the index case household and six closest, consenting households will receive 
IRS with Actellic CS.  
Primary 
outcome 
Incidence of confirmed, passively detected local malaria cases in each study 
arm, captured at study health facilities, that are reported via the rapid reporting 
system by enumeration area. 
Secondary 
outcomes 
<0000> 
Prevalence of infection, among all age groups, as measured by LAMP 
<0000> Seroprevalence of infection, among all age groups, as measured by ELISA 

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<0000> Coverage of the intervention. Case intervention coverage is the proportion 
of eligible cases investigated of the eligible cases reported in the Rapid 
Reporting System. For both RACD/RfMDA, the proportion of eligible 
participants enrolled per intervention up to 25 out of the number of eligible 
residents within 500 meters of the index case household up to 25 per 
intervention. For RACD, the proportion of the population living in the 
Target Area that receives a finger prick to test for malaria. For RfMDA, the 
proportion of participants that receive an initial dose of antimalarial drug 
(intention to treat analysis) per intervention up to 25 per intervention out of 
the number of eligible residents within 500 meters of the index case 
household up to 25 per intervention. For RAVC, proportion of targeted 
houses that receive IRS up to seven per intervention out of the number of 
households within 500 meters of the index case up to seven per intervention. 
<0000> Index case household coverage. Proportion of eligible participants in 
the index household receiving the intervention out of the number of 
eligible residents of the index household 
<0000> Number of serious adverse events (SAEs) related to antimalarial treatment 
or additional IRS. 
<0000> Acceptance as evaluated by participation rate in each of the combinations 
of interventions and by qualitative assessment. 
<0000> Costs per intervention episode, and per case averted. 
<0000> Medication adherence, as measured by pill count. 
Evaluation 
methods 
The primary outcome measure is malaria incidence in each study arm, passively 
detected at health facilities and confirmed by RDT or slide. These data will be 
obtained through routine surveillance data from the MoHSS surveillance 
system, where cases are reported via tablet within 24 hours. These data will 
then be fed into the spatial decision support system (SDSS) to geo-locate them 
and support intervention planning. 
Other secondary outcome evaluation methods: 
1) Prevalence and seroprevalence will be assessed through a cross sectional 
household survey in a sample of residents of all intervention EAs at study 
conclusion. RDTs will be conducted, DBS will be collected, an interview 
conducted, and molecular testing and serology performed.  
2) Incidence beyond the period of the study intervention wil also be assessed 
to determine if community level impact is delayed or sustained. 
3) Coverage of RACD or RfMDA in the target population will be measured by 
comparing number of participants receiving the intervention (up to 25 per 
intervention) to the baseline population data of residents within 500 meters 
of index case households (up to 25 per intervention) available from Phase I 
(Geographical reconnaissance study). 
4) Serious adverse event (SAE) reports will be assessed during Pill Counts, and 
through spontaneous reports by participants. 
5) Adherence will be assessed by a pill count follow-up in select Target Areas. 
6) Costing and cost-effectiveness data will be collected during study 
implementation in 2017. 
7) Acceptability will be assessed through quantitative measurement of trial 
participation and the endline survey, and through qualitative assessment in 
focus group discussions and key stakeholder interviews. 

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Sample size 
The sample size is based on prior incidence from study area. Of the 102 EAs, 
incidence data are not yet available in 29. Additionally a further 19 had no cases 
in the previous 3 years. This leaves a remaining 54 EAs available. In order to 
have equal EA numbers in each arm we have included 56 total EAs (including 
2 EA with no incident cases), each of which will be randomized to one of the 
four intervention arms. The final EA list includes 14 EAs each for the 4 study 
arms. 
Population size is unequal across different potential EA sets, thus sample size 
for power calculations is based on an effective sample size adjusted for this 
variation. The current set of 56 EAs has a harmonic mean of 276 people in each 
EA, for a total effective sample size of 15,456. For the primary objectives, we 
hypothesize that introduction of RACD alone (control condition for this study) 
will result in an incidence of 25 per 1000 population per year compared to the 
current 33 per 1000 population per year rate observed with limited active follow 
up.  
We hypothesize that RfMDA and RAVC will each be associated with a 50% 
reduction in annual malaria incidence compared to RACD only, and that the 
combination of RfMDA and RAVC will be associated with a 75% reduction 
compared to RACD only, assuming no interaction. With the above sample size 
and assumptions regarding effect size, this study has at least 80% power to 
detect the hypothesized differences between RfMDA versus RACD, RAVC 
versus no RAVC, and the combination of RfMDA and RAVC versus RACD 
only.   
Incidence of confirmed, passively detected cases will be captured through the 
existing surveillance system, and those occurring in study EAs identified. 
Secondary outcome measures for infection prevalence and seroprevalence will 
be measured in an estimated 5,040 people in the endline cross sectional survey. 
Other secondary outcome measures will be captured among people enrolled for 
RACD or RfMDA activities over the course of the study. 
Study Design 
 
RfMDA vs RACD arms 
 
 
RACD 
(28 
clusters): 
RfMDA 
(28 
clusters): 
 
No RAVC (28 
clusters): 
RACD (14) 
RfMDA (14) 
 
RAVC vs       
no RAVC 
arms 
RAVC (28 clusters): RACD + RAVC 
(14) 
RfMDA + RAVC 
(14) 
 
 
 

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Key Personnel 
Principal Investigators 
Davis Mumbengegwi, PhD  
Deputy Director, and Head of Division of Science, 
Technology and Innovation, Multidisciplinary Research 
Centre, University of Namibia 
Email: dmumbengegwi@unam.na   
Phone: +264 (0) 61-206-3908 
Dr. Mumbengegwi will provide local oversight of the project, 
with a focus on data collection and laboratory procedures. He 
will ensure compliance with standard procedures, and 
contribute to study design, data analysis, and manuscript 
writing. He will co-supervise project staff with the Program 
Manager. 
Michelle Hsiang, MD  
Deputy Lead, Operational Research, Malaria 
Elimination Initiative, Global Health Group  
Assistant Adjunct Professor, Pediatric Infectious 
Diseases, Dept of Pediatrics 
University of California, San Francisco 
Assistant Professor, Pediatric Infectious Diseases, Dept 
of Pediatrics, University of Texas Southwestern 
Medical Center 
Email: Michelle.Hsiang@UTSouthwestern.edu 
Phone: +1-415-595-5978 
Dr. Hsiang will be responsible for general leadership and 
oversight of the project. She will lead study design, provide 
oversight of standard operating procedures in the field and 
laboratory, and lead data analysis and manuscript writing.  
Roly Gosling, MD, PhD  
Associate Professor, Dept. of Epidemiology and 
Biostatistics 
Lead, Malaria Elimination Initiative, Global Health 
Group, University of California, San Francisco 
Email: Roly.Gosling@ucsf.edu 
Phone: +1-415-597-8114 
Dr. Gosling will be responsible for oversight of the project, 
including study design, partner management, funder liaison, 
and manuscript preparation. He will align study activities 
with other Global Health Group supported activities in 
malaria elimination. 
Jennifer Smith, PhD 
Postdoctoral Fellow 
Malaria Elimination Initiative, Global Health Group, 
University of California, San Francisco 
Email: Jennifer.Smith@ucsf.edu   
Phone: +1-415-597-9247 
Dr. Smith will participate in study design, data collection 
management, data analysis (particularly with spatial 
analyses), and manuscript writing. 
Immo Kleinschmidt, PhD 
Professor of Epidemiology, Department of Infectious 
Disease Epidemiology, London School of Hygiene and 
Tropical Medicine 
Email: immo.kleinschmidt@lshtm.ac.uk   
Phone: +44(0)20 7927 
Dr. Kleinschmidt will lead targeted vector control aspects of 
the project, including experimental design, data collection, 
analysis, and manuscript preparation  
Adam Bennett, PhD 
Networks Lead 
Malaria Elimination Initiative, Global Health Group, 
University of California, San Francisco 
Email: Adam.Bennett@ucsf.edu 
Phone Number: +1 415 597 4981 
Dr. Bennett will participate in study design, data analysis 
(including spatial analysis), and manuscript writing. 
Co-Investigators 
Petrina Uusiku, MD 
Chief Medical Officer, National Vector-borne Diseases 
Control Programme, Ministry of Health and Social 
Services 
Email: uusikup@nacop.net   
Phone: +264-811-462-707 
Dr. Uusiku will support aspects of the project supported by 
the National Vector-borne Diseases Control Programme 
(NVDCP). She will provide input on study design, 
coordination, and manuscript preparation. She will ensure 
that study findings inform future program planning and 
implementation as indicated. 
 
Stark Katokele, MSc 
Parasitologist, National Vector-borne Diseases Control 
Programme, Ministry of Health and Social Services 
Email: katokeles@nacop.net   
Phone:+264-812-928-754 
Mr. Katokele will support surveillance aspects of data 
collection. He will provide support to the Research 
Coordinator in her work with regional and district NVDCP 
staff to ensure quality data collection. He will help the 
Research Coordinator troubleshoot when issues arise.  

Reactive Targeted Parasite Elimination to Reduce Malaria in Zambezi Region, Namibia 
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Ronnie Bock, PhD 
Senior Lecturer,  Dept. of Biological Sciences 
University of Namibia 
Email: rbock@unam.na   
Phone: +264 (0) 61-206-3234 
Dr. Bock will support data collection and laboratory 
procedures. He will assist with field and student supervision. 
Kathryn Roberts, MPH 
Namibia Project and Research Coordinator, Malaria 
Elimination Initiative, Global Health Group, University 
of California, San Francisco 
Email: Kathryn.Roberts@ucsf.edu 
Phone: +264-81-277-4407 
Based in Namibia, Ms. Roberts will oversee the fieldwork, 
co-supervise 
study 
staff, 
and 
manage 
partner 
communications. She will ensure that the goals and 
procedures of the study align with policies and guidelines of 
the Namibia Ministry of Health and Social Services. She will 
collaborate on study design, data collection, analysis, and 
manuscript preparation. 
Lisa Prach, PhD, MPH 
Research Specialist 
Malaria Elimination Initiative, Global Health Group, 
University of California, San Francisco 
Email:Lisa.Prach@ucsf.edu 
Phone: +1-415-476-5929 
Dr. Prach will support the field coordination of the clinical 
trial, including study tools, site supervision, data collection, 
analysis, and manuscript preparation. She will also lead the 
cross-sectional endline survey in 2017. 
Oliver Medzihradsky, MD, MPH, MSc 
Research Fellow 
Division of Pediatric Infectious Diseases 
Department of Pediatrics, UCSF 
Email:olivermed@ucsf.edu 
Phone: +1-530-318-3273 
Dr. Medzihradsky will lead the serology sub-study. He will 
also support the field coordination of clinical trial, the data 
safety monitoring board, and providing ongoing monitoring 
of adverse events. 
Bryan Greenhouse, MD, MA 
Assistant Professor, Division of Infectious Diseases, 
Department of Medicine, University of California, San 
Francisco 
Email: bgreenhouse@medsfgh.ucsf.edu   
Phone: +1-415-206-8844 
Dr. Greenhouse will lead genotyping and will work with Dr. 
Mumbengegwi and his lab to support other laboratory related 
aspects of the project including PCR and serology.  
Collaborators 
 
Mi-suk Kang Dufour, PhD 
Assistant Professor 
Division of Prevention Science 
University of California, San Francisco 
Email: mi-suk.kangdufour@ucsf.edu 
Phone: +1-415-476-6287 
Dr. Dufour will provide statistical support in the study design 
and analysis.  
Patrick McCreesh, MS 
Data Manager 
University of Texas Southwestern Medical Center and 
University of California, San Francisco 
Email: Patrick. McCreesh@utsouthwestern.edu 
Mr. McCreesh will provide administrative support for 
UTSW-led activities and support data cleaning and analysis. 
Brooke Whittemore, MPH 
Data Manager 
University of Texas Southwestern Medical Center 
Email: Brooke.whittemore@utsouthwestern.edu 
Ms. Whittemore will provide administrative support for 
UTSW-led activities and support data cleaning and analysis. 
Maxwell Murphy 
Laboratory Coordinator 
Division of Infectious Diseases, Department of 
Medicine, University of California, San Francisco 
Email: Maxwell.Murphy@ucsf.edu 
Phone: +1- 707-364-7044 
Mr. Murphy will support the coordination of laboratory 
related aspects of the study. Will provide trainings, help 
coordinate sample transport and storage, ordering of supplies, 
troubleshooting in the lab, and will perform assays as needed. 
Kim Baltzell, MS, PhD 
Associate Professor - Department of Family Health 
Care Nursing, UCSF 
Phone: +1-415-215-7701 
Email: kimberly.baltzell@ucsf.edu 
Dr. Baltzell will support the study design and analysis of the 
qualitative acceptability study. 
Bradley Didier, MPH 
Mr. Didier will support collaboration between the Global 
Health Group, the Ministry of Health and Social Services, and 

Reactive Targeted Parasite Elimination to Reduce Malaria in Zambezi Region, Namibia 
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Program Manager, Malaria Technical Support Clinton 
Health Access Initiative  
 
CHAI. He will provide guidance in study coordination, data 
collection, and input on data analysis, and translation of study 
findings into program planning and implementation, as 
indicated.  
Zaahira Gani. MSc 
Project Manager, Novartis Foundation  
Email: zaahira.gani@novartis.com 
Ms. Gani will support project implementation 
through protocol and strategy review, and 
facilitating the relationship between the study and 
the Foundation.  
Michael Reddy 
Malaria – Vector Control Program Officer 
The Bill & Melinda Gates Foundation 
Michael.reddy@gatesfoundation.org 
Mr. Reddy will support reactive vector control design, 
implementation, and review, and facilitate the relationship 
between the study and the Foundation. 
Munyaradzi Tambo, MS 
Laboratory Technologist, University of Namibia 
Phone: +264-81-4349435 
Email: munyaradzitambo@yahoo.com 
Mr. Tambo will be responsible for running all the samples 
that are processed in Windhoek under the direction of Dr. 
Mumbengegwi. 
Henry Ntuku, PhD 
Postdoctoral Fellow in Randomized Controlled Trial 
Implementation 
Katima Mulilo, Namibia 
Dr. Ntuku will be responsible for technical oversight of trial 
implementation including protocol review, training, field 
supervision, data management, and analysis. 
Smita Das 
Scientific Laboratory Associate 
PATH 
Email: SDas@path.org 
Phone: +1-206-285-3500 
Ms. Das will coordinate the quantitative HRP II concentration 
assays running and analysis. 
Gonzalo Domingo, PhD 
Scientific Director, Malaria Diagnostics 
Diagnostics Program, PATH 
Email: gdomingo@path.org 
Tel: +1-206-285-3500 
Dr. Domingo will provide support to laboratory activities to 
quantitate parasite-specific antigen concentration and ensure 
alignment of study with other diagnostics studies at PATH. 
Jade Benjamin-Chung, PhD MPH 
Epidemiologist and Lecturer 
Division of Epidemiology 
University of California, Berkeley 
Email: jadebc@berkeley.edu 
Dr. Benjamin Chung will work with the Principal 
Investigators and Dr. Dufour to support secondary analyses, 
specifically in the area of measuring indirect or spillover 
effects of the study intervention. 
Mark van der Laan, PhD 
Professor 
Department of Statistics 
University of California, Berkeley 
Email: laan@stat.berkeley.edu 
Dr.. van der Laan will lend his expertise and will mentor Dr. 
Benjamin-Chung in spillover effects analysis using machine 
learning. 
John Marshall, PhD 
Assistant Professor 
Division of Epidemiology 
University of California, Berkeley 
Email: john.marshall@berkeley.edu 
Dr. Marshall will lend his expertise in modeling to co-mentor 
Dr. Benjamin-Chung in spillover effects analysis. He will 
also supervise UC Berkeley students to use modeling assess 
the effectiveness of RACD.  
Sean Wu, BA, MPH 
PhD candidate 
Division of Epidemiology 
University of California, Berkeley 
Email: slwu89@berkeley.edu 
Mr. Wu will support modeling analyses on the effectiveness 
of RACD and be mentored by Dr. Marshall. 
Hector M. Sanchez, PhD 
Post doctoral fellow 
Division of Epidemiology 
University of California, Berkeley 
Email: sanchez.hmsc@gmail.com 
Dr. Sanchez will support modeling analyses on the 
effectiveness of RACD and be mentored by Dr. Marshall. 
Jared Bennett, BSc 
PhD candidate, Biophysics and Computational Biology 
University of California, Berkeley 
Mr. Bennett will support modeling analyses on the 
effectiveness of RACD and be mentored by Dr. Marshall. 

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Email: jared_bennett@berkeley.edu 
Hugh Sturrock, PhD 
Assistant Professor, 
Epidemiology and Biostatistics 
Malaria Elimination Initiative, Global Health Group, 
University of California, San Francisco 
Email: hugh.sturrock@ucsf.edu 
Dr. Sturrock will support secondary analyses of malaria risk. 
He will supervise Amanda Irish. 
Amanda Irish, DVM, MPH 
PhD candidate, Epidemiology and Biostatistics 
Malaria Elimination Initiative, Global Health Group, 
University of California, San Francisco 
Email: Amanda.irish@ucsf.edu 
Dr. Irish will perform secondary analyses of malaria risk. 
 
 
Partners and qualifications 
The University of California (UCSF) Global Health Group, The University of Namibia (UNAM) 
Multidisciplinary Research Centre, The Ministry of Health and Social Services’ (MoHSS) National 
Vector-borne Diseases Control Programme (NVDCP), the University of Texas Southwestern Medical 
Center (UTSW), the London School of Hygiene and Tropical Medicine (LSHTM), and the Clinton 
Health Access Initiative (CHAI) collaborated on a project in the Ohangwena and Omusati regions of 
Namibia to evaluate reactive case detection (RACD) beginning in 2012. Building on this work, the 
partners will work together in Zambezi region to evaluate  targeted parasite elimination (TPE) as a 
strategy to interrupt malaria transmission. The project includes two phases: Phase I focused on building 
surveillance and response capacity and understanding local malaria epidemiology; Phase II involves 
implementation and evaluation of the effectiveness and feasibility of TPE.  
The expertise of NAMEP partner organizations is described below: 
Malaria Elimination Initiative, Global Health Group, UCSF 
The Global Health Group at UCSF is an ‘action tank’ dedicated to translating new approaches into 
large-scale action that improves the lives of millions of people. The UCSF Global Health Group’s 
Malaria Elimination Initiative (MEI) believes that global eradication of malaria is possible within a 
generation. Working with partners at global, regional, and national levels, the MEI accelerates progress 
by conducting operational research to improve surveillance and response, determining the costs of 
elimination, and strengthening political and financial commitment to shrink the malaria map.  
Multidisciplinary Research Centre, University of Namibia 
The MRC at UNAM works to implements applied research activities in priority areas. In 2011, the 
MoHSS mandated UNAM to conduct operational research on the Ministry’s behalf, to achieve the 
regional RBM network’s objective of malaria elimination. The MRC is a research hub conducting 
collaborative research with partners from UNAM faculty and local, regional, and international 
partners. The MRC will serve as a sub-grantee, managing funds for in-country implementation, 
including hiring and managing project staff, and processing samples in their bio-molecular research 
laboratory. 
National Vector-borne Diseases Control Programme, Ministry of Health and Social 
Services 
The National Vector-borne Diseases Control Programme (NVDCP) is a unit of Namibia’s Ministry of 
Health and Social Services (MoHSS). The NVDCP is tasked with addressing vector-borne illnesses, 
including malaria, through surveillance, environmental control measures, and outbreak response. The 
NVDCP will guide the project design to ensure MoHSS goals are addressed and new interventions are 
scalable. Regional NVDCP and project staff will work together in Zambezi region, helping lead the 
implementation of this project.  

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The University of Texas Southwestern 
The University of Texas Southwestern (UTSW) Medical Center is a leading biomedical institution 
devoted to clinical care as well as multidisciplinary research and scientific training in both basic and 
clinical research. Through a grant from the Horchow Family Fund, is supporting study design, 
oversight, implementation, and analysis. 
 
 
The London School of Hygiene & Tropical Medicine 
The London School of Hygiene and Tropical Medicine is a world-leading centre for research and 
postgraduate education in public and global health. Their mission is to improve health and health equity 
in the UK and worldwide, working in partnership to achieve excellence in public and global health 
research, education and translation of knowledge into policy and practice. The Malaria Centre at the 
London School of Hygiene & Tropical Medicine develops tools, techniques, and knowledge about 
malaria, with a strong emphasis placed on translating research outcomes into practice, including 
diagnosis and treatment. 
The Clinton Health Access Initiative 
The Clinton Health Access Initiative (CHAI) works to improve markets for lifesaving medicines and 
diagnostics, lower the costs of treatments, and expand access to life-saving technologies – creating a 
sustainable model that can be owned and maintained by governments. In Namibia, CHAI has a long-
standing relationship with the MoHSS and the NVDCP to support their malaria program. CHAI will 
contribute to protocol development, capacity building, implementation, and is a coordinating partner 
for the project. 
University of the Witwatersrand 
The University of the Witwatersrand is a multi-campus South African public research university 
situated in the northern areas of central Johannesburg. For this study, the University of Witswatersand 
will be supporting the implementation and evaluation of the Reactive Vector Control (RAVC) 
intervention and entomological monitoring. 
PATH 
PATH is an international, nonprofit global health organization, which drives transformative innovation 
to save lives and improve health, especially among women and children. PATH will perform 
quantitative HRP II assays for this study and will contribute to manuscript writing. 
 
University of California, Berkeley 
The University of Berkeley School of Public Health is a leading global and public health institution 
with particular strengths in epidemiological methods.  As such, they will lend expertise in spillover 
analyses modeling to the study. 
 
The Novartis Foundation  
The Novartis Foundation, a private sector foundation, takes a strategic approach and works to create 
sustainable health service models and improve access to healthcare for those most in need, leveraging 
its on-the-ground experience and partnerships on projects addressing an unmet need bringing solutions 
to public health problems. The foundation explores innovative interventions and measurements to 
bring the world closer to the eventual goal of leprosy and malaria elimination. The Novartis Foundation 
is a partner as well as a funder, providing valuable input for project design and implementation based 
on extensive experience in malaria in the developing world. 
 
 
The Bill and Melinda Gates Foundation 

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The Bill and Melinda Gates Foundation is the largest private foundation in the world. The primary 
aims of the foundation are, globally, to enhance healthcare and reduce extreme poverty. For this study, 
the Foundation will be supporting the evaluation of the Reactive Vector Control (RAVC) and 
entomological monitoring, through a grant to Wits University. 
 
 
 
 
 
 
 
 
 
1.0 Background 
1.1 Namibia Malaria Elimination Research Partnership (NAMEP) 
As a result of successful malaria control efforts, Namibia, like many countries in southern Africa, is 
aiming for elimination by 2020.1 The National Vector-borne Diseases Control Programme (NVDCP) 
of the Ministry of Health and Social Services (MoHSS) and the Southern African Regional Network 
of the Roll Back Malaria have identified surveillance research and strengthening as key determinants 
for the future of malaria control and elimination in the region. The NVDCP has asked the University 
of Namibia (UNAM) to support its malaria elimination aims through operational research. UNAM is 
interested in leading such research and further developing its capacity to study malaria in the low 
transmission setting of Namibia. The University of California, San Francisco (UCSF), the London 
School of Hygiene and Tropical Medicine (LSHTM), and the Clinton Health Access Initiative (CHAI) 
are established partners of the NVDCP and UNAM, collaborating to build the evidence base for 
malaria elimination strategies and decision-making.  
Beginning in 2012, the partners conducted malaria elimination research in the Ohangwena and 
Omusati regions of Namibia, including implementing reactive case detection (RACD). Building on 
this work, the NVDCP, UNAM, UCSF, LSHTM, CHAI, the Bill and Melinda Gates Foundation, and 
the Novartis Foundation worked together during Phase I of this project to build surveillance and 
response capacity and better understand the epidemiology of malaria in the region. In Phase II of the 
project these partners have built on the findings from Phase I to implement a randomized controlled 
trial comparing RACD, the current standard response to a passively detected malaria case, to reactive 
focal mass drug administration (rfMDA) or presumptive treatment without testing in response to an 
index case. Additionally, the study will evaluate whether reactive indoor residual spraying (IRS) in 
response to index cases, in conjunction with RACD or RfMDA, provides an additional benefit.  
1.2 Malaria Elimination in Namibia 
Namibia has experienced a tremendous decrease in reported malaria cases, from 538,512 cases in 2001 
to 4,593 in 2013. Ongoing interventions, such IRS, LLIN distribution, and the introduction of rapid 
diagnostic tests (RDTs) and artemisinin combination therapy (ACT), have contributed to this decline. 
During the same period, malaria deaths decreased by 98 percent from 1,728 per year to 36, far 
surpassing targets to reduce malaria-related deaths by 50 percent. However, recently the success has 
stalled, with 15,692 cases and 61 deaths in 2014 and 12,045 cases and 43 deaths in 2015. In 2016, the 
MoHSS declared a malaria outbreak, with the final number of cases, to be released in 2017, expected 
to exceed any of the previous years. New strategies are needed to re-establish progress towards malaria 
elimination. This study will explore a promising new elimination strategy, targeted parasite elimination 
(TPE) of the parasite reservoir in humans and the mosquito, to evaluate its effectiveness, and determine 
its operational feasibility, acceptability, and cost and cost effectiveness. 

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The path to malaria elimination must include a shift in focus, from reducing the clinical burden of 
malaria to interrupting transmission, from only focusing on symptomatic infections to including 
asymptomatic infections as a priority. Since malaria transmission is highly geographically 
heterogeneous, elimination activities must target hotspots or areas where the risk of future infection is 
highest. In the transition from control to elimination, real-time surveillance and rapid response are 
necessary to target hotspots with interventions to interrupt transmission.2  
 
Reactive Case Detection 
Reactive case detection (RACD), which includes testing and treatment around passively detected 
cases, is a recommended elimination strategy to identify secondary cases and hot spots.3–5However, 
RACD can be labour, time, and cost intensive, and misses people who are absent during screening or 
refuse to have their blood drawn.3 Microscopy is being replaced by antigen-based RDTs that provide 
convenience, rapid results, and reduce the need to rely on microscopists, but have limited sensitivity 
to detect low parasite density and non-falciparum infections.6,7 Polymerase chain reaction (PCR) offers 
markedly improved sensitivity, but requires hours of processing time, sophisticated technical skills, 
and expensive equipment. Loop mediated isothermal amplification (LAMP) offers the sensitivity of 
PCR and is easier to perform, but because samples must be analysed in a laboratory, its usefulness for 
community-level screening and treatment is limited. How to detect both symptomatic and 
asymptomatic infections in a field setting continues to present a challenge for malaria elimination. 
Namibia’s malaria guidelines include notification of cases within 24 hours via a rapid reporting system, 
investigation of all cases, conducting RACD at the community level, treatment of any positives, 
provision of health education, and reporting of any additional RDT-detected malaria cases. However, 
currently, it is not possible to conduct RACD for each malaria case in Zambezi region because of the 
high malaria burden.  
In a case-control evaluation of RACD in Engela, Oshikuku, and Outapi districts, in Namibia, 
asymptomatic infections were more likely to occur near the homes of passively detected index cases 
compared to randomly selected controls. Using highly sensitive LAMP testing, among case 
neighbourhoods 64 secondary cases were found among 1,518 people (4% positivity rate) versus only 
two secondary cases found among 1,129 people screened in control neighborhoods (0.18% positivity 
rate). RDTs detected only 24 of the 64 (38%) secondary cases that were later identified by LAMP, 
indicating that RDTs are not sensitive enough to identify all cases of malaria. This is likely because 
standard RDTs are designed to detect symptomatic illness, where people are likely to have a higher 
density of parasites, rather than to detect asymptomatic or low-density infections (Sturrock, 
unpublished).  
UCSF’s collaboration with the Swaziland National Malaria Control Programme and CHAI to evaluate 
RACD in Swaziland has yielded similar findings. RDTs were shown to detect about 20% of 
asymptomatic infections when compared to PCR as the gold standard. As in Namibia, infections 
clustered around households of index cases, with those living within 200 metres of the index case at 
higher risk than those living from 200-500 metres away. (Hsiang et al, in preparation)  
 
1.3 Reactive focal mass drug administration (rfMDA) 
Given the limitations of RACD to identify low-density infections, the logistical challenges and cost 
associated with the screening process, presumptive treatment leveraging the reactive surveillance 
infrastructure of RACD may be a more feasible and effective strategy to reduce and interrupt 
transmission in certain settings.  
RfMDA, a form of mass drug administration, or presumptive treatment, has been used successfully in 
China to overcome some of the weaknesses of RACD.8In a low transmission setting, only a small 

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proportion of the population is at high risk of infection, therefore, only a small number of people need 
to be targeted. RfMDA targets remaining reservoirs of infection in low endemic settings by treating 
everyone at high risk (subjects residing around an index case), rather than rely on RDT results, which 
have been shown to miss infections. Additional indoor residual spraying (IRS) targeted to homes in 
high risk locations can also be implemented. For presumptive treatment to be effective, mathematical 
modelling suggests that 80 - 90% of the population must be covered.10 This is made easier by 
accurately targeting small, limited populations.  
 
1.4 Reactive case detection (RACD) vs. reactive focal mass drug administration (rfMDA) 
RfMDA is a promising strategy, but evidence does not yet exist to prove its efficacy in 
Africa.9Questions remain about where to target it, what drugs to use, and whether drugs should be used 
alone or in combination with additional vector control. There are questions about the acceptability to 
the community, costs and cost effectiveness, operational feasibility, and the sustainability of the 
impact. The advantages, disadvantages, and uncertainties around reactive case detection versus rfMDA 
are summarized in Table 1. 
 
Table 1. RACD vs rfMDA 
 
 
RACD 
rfMDA 
Rationale 
Identification/tre
atment low-
density 
infections 
- Misses low density infections 
+ Prophylactic effect in those treated, 
depending on half-life of medication 
used 
+ Does not rely on insensitive diagnostics 
+ May provide prophylactic effect to entire target 
population, depending on half-life of medication 
used 
Effectiveness 
Effectiveness to 
decrease 
transmission 
? Not well established 
? Not well established 
Coverage of 
intervention 
+/- High acceptability facilitates good 
coverage, but logistics of testing 
make high coverage challenging 
? Ease of giving medication without testing may 
facilitate high coverage at first encounter 
Acceptability 
+/- Acceptability high, but occasional 
refusals due to community dislike for 
blood tests 
+/-  Anticipate some refusals to take medication, 
but acceptability may be high due to previous 
experience with malaria and knowledge of the 
medication’s prophylactic effect 
Safety using 
ACT 
+ Treatment of only test positive 
people is safe 
+ Treatment of many asymptomatic people is 
likely to be safe  
Safety using 
additional IRS 
+ Likely to be safe 
+ Likely to be safe, no evidence to suggest 
increased toxicity when used with antimalarials 
Adherence to 
drug regimen 
+ Adherence among persons with 
known infection likely to be good  
-  Adherence among persons without known 
infection may be poor without some sort of 
directly observed therapy 
+ Adherence may be good if treatment course is 
simple and short, perceived risk of malaria is high, 
and prophylactic effect is understood 
Feasibility 
 
Cost-
effectiveness 
? Cost and time necessary to only 
treat vs screen and treat has not been 
measured, but as rfMDA treats 
asymptomatic infections, a reservoir 
for infection, the cost per case averted 
may be lower. 
? Relative cost-effectiveness compared to the 
standard of care (RACD) is not known. 
 
1.5 Drug Administration 
The goal of presumptive treatment is to treat community members presumptively to eliminate any 
existing reservoir of malaria infection. For this study, we use artemether-lumefantrine (AL or 
Coartem), an artemisinin-based combination therapy (ACT) that is the first line treatment for 
uncomplicated Plasmodium falciparum malaria in Namibia and has been approved for use in over 80 
countries. AL has proven safe and effective against uncomplicated malaria.10 
The transmission blocking potential for AL has been described.11–13In asymptomatic populations, it 
has been evaluated for presumptive treatment among children with severe anemia (monthly for three 

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months)14, and found to be safe but not effective at reducing individual malaria risk. It has also been 
evaluated for mass screening and treatment among individuals of all ages.15,16 In these studies, AL was 
shown to be well tolerated and safe with no severe adverse events, but not effective for reducing 
malaria transmission. These studies were challenged by their high transmission settings, and the 
screening and treatment studies were additionally limited by the poor sensitivity of RDTs to detect 
low-density infections. The use of AL for focal presumptive treatment in a lower transmission setting 
such as Namibia, has a higher potential to be effective at transmission reduction.  
AL dosing is weight adjusted, allowing for pediatric dosages (Appendix I). Regardless of age, the 
second dose is administered eight hours after the first dose. Beginning the next day, a dose is given 
twice daily, approximately 12 hours apart, for two consecutive days. Due to insufficient data, the 
manufacturer of AL recommends it not be administered to infants weighing less than 5kg or younger 
than two months. Namibia’s National Malaria Case Management Guidelines, authored by the MoHSS, 
sets a more conservative minimum age of 6 months for AL, in addition to the minimum weight of 5kg. 
First trimester pregnancy is a contraindication, based on animal studies suggesting that foetal 
absorption could lead to early pregnancy loss. The additional contraindications to AL in the MoHSS 
national malaria policy, include complicated/severe malaria, prior allergic reaction to AL, and 
conditions that predispose the patient to prolongation of the cardiac QT interval.  The latter include a 
personal history of cardiac dysrhythmia, a family history of prolonged QT syndrome, or concurrent 
medications that are known to prolong the QT interval. Cardiac QT prolongation is a known class 
effect of numerous antimalarial drugs. Notably, in a recent review of nine different clinical trials using 
AL-based regimens, no serious adverse events (e.g., syncope or sudden cardiac death) were found to 
be associated with AL administration. 
AL is active against early gametocytes, therefore the drug has some transmission blocking effect. The 
addition of single dose primaquine (PQ), which is effective against gametocytes of all stages, has the 
potential to block transmission. For uncomplicated Pf malaria cases, the latest National Malaria Case 
Management Guidelines for Namibia indicate a new policy to give single dose PQ the first day of 
treatment, in addition to AL.  Per national policy, single dose PQ will be provided to Pf index cases in 
the study as well as household members and neighbours of index cases who are tested with an RDT 
and found to have uncomplicated Pf malaria infection.  This will be all positive RDTs in the RACD 
arm, and anyone who is excluded from rfMDA, receives an RDT instead, and tests positive. Those 
receiving TP will not receive PQ. 
Dihydroartemisinin-piperaquine (DP) is another safe and effective ACT regimen recommended by the 
World Health Organization (WHO), and is recommended as a second line therapy for uncomplicated 
malaria in many countries.10,17–21 The drug is also considered to be an ideal drug for presumptive 
treatment due to the long prophylactic effect on new infections that may last for up to 63 days (PCR-
unadjusted treatment failure: RR 0.71, 95% CI 0.65 to 0.78, two trials, 3200 participants, high quality 
evidence). In addition, dosing is once daily instead of twice daily as with AL.11The decision about 
using DP vs AL was discussed extensively with partners in this study and it was felt that DP was not 
an option because the drug is not registered in Namibia. Additionally, partners expressed concern about 
using a drug with a longer half-life, and the potential for drug resistance, given some recent reports 
from Southeast Asia of decreased efficacy of DP.22 
It has been proposed that presumptive treatment should be administered by directly observed therapy 
(DOT), because high coverage is critical to success. People who are not ill may be less adherent to 
medication; however, adherence may be higher when the perceived risk of infection is high, as would 
be the case in this study, where a family member or neighbour will have been diagnosed with malaria 
recently. In a review of the 12 successful trials that utilized mass drug administration, six employed 
DOT or modified DOT. Drug distribution and observation was performed by community volunteers, 
local health workers, study authors and/or external organizations.23While strict DOT would ensure the 

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highest adherence, it may not be practical for under-resourced malaria programmes, particularly during 
high transmission season when malaria staff are busy. Many people may be away at school or work 
during the day, making strict DOT challenging. In this study, we will utilize modified DOT, where the 
first dose is directly observed and reminders for subsequent doses will be provided by family and 
community members, and the study staff when they are conducting follow-up visits to improve 
coverage. Adherence will be assessed by pill count in people treated in the RACD arm and a sub-set 
of people treated in the RfMDA arm. 
 
1.6 Reactive Vector Control (RAVC)  
Namibia’s malaria control strategy principally relies on vector control using indoor residual spraying 
(IRS). The MoHSS conduct IRS between October and December each year using 
dichlorodiphenyltrichloroethane (DDT) on traditional structures and deltamethrin (a pyrethroid) on 
modern structures with cement-plastered surfaces. As is common in areas with lower rainfall, the main 
vector in Namibia is Anopheles arabiensis. Standard, annual WHO susceptibility testing at a number 
of sentinel sites indicates that the vector remains highly susceptible to DDT and deltamethrin. A first 
limitation is that the single annual round of IRS, as currently practised, misses many houses because 
structures may be locked, households may refuse, or the spray round may not reach all communities. 
Second, although high quality application of insecticide is intended, it is difficult to guarantee 
consistent spray quality. Finally, to delay or prevent insecticide resistance it would be necessary to 
rotate insecticides of either the organophosphate or carbamate class, because these have a different 
mode of action than pyrethroids and DDT.24 
For RfMDA to be most successful it is necessary to kill parasites in human hosts as well as the vector 
population of the target area. This will be achieved only if RfMDA includes a reactive vector control 
(RAVC) component. The malaria control programmes in many low transmission countries target IRS 
where they perceive malaria risk to be highest. Such targeting is driven, in part, by pragmatic factors 
related to insecticide cost, yet it also facilitates supervision and quality control. To be most effective, 
IRS targeting will be directed at foci with active transmission. 
Long lasting micro-encapsulated pirimiphos-methyl (Actellic® 300 CS; Syngenta, Basel, Switzerland) 
has been shown to be highly effective as a residual insecticide against A. arabiensis, killing high 
proportions of mosquitoes for up to 12 months.25 Reactive and focal spraying with Actellic 300 CS 
can provide high quality vector control in places where ongoing transmission exists or is likely. The 
long-lasting residual effect will ensure that inward migrating mosquitoes are unlikely to survive. The 
targeted nature of RAVC will facilitate a high degree of quality, which may help compensate for 
possible shortcomings in the annual IRS campaign. As an insecticide of the organophosphate class, 
Actellic will not contribute to the selection pressure for resistance that is exerted by the current use of 
DDT and pyrethroids in Namibia.25 
 
2.0 Rationale 
2.1 Overall rationale  
RACD may identify asymptomatic infections and hotspots, but there are logistical challenges such as 
specimen collection, laboratory testing, and the need to return to treat people who were negative by 
RDT but positive by molecular testing, which can lead to loss of follow-up. Molecular detection 
methods that are more sensitive than RDT or microscopy are costly, require significant laboratory 
expertise, and may still miss very low parasite density infections. Additionally, using molecular tests 
for diagnosis has not been sanctioned by the WHO, and therefore national programmes might be 
hesitant to use them. By eliminating the need to test people prior to treatment, RfMDA may be more 
feasible to implement and more effective. 
For rfMDA to be effective it is necessary to kill parasites in the human and vector populations in the 
target area. However, one challenge of targeted pre-transmission season IRS is that it is difficult to 

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predict where future infections will occur. A reactive approach, in conjunction with the pre-
transmission approach, will ensure IRS coverage in the highest risk areas. Further, if there is unknown 
resistance to the insecticide used during pre-transmission season, the subsequent reactive use of a 
different, and presumably effective insecticide, will provide better protection. 
2.2 Rationale for the study design and selected study outcomes 
In this study, we will utilise a cluster randomized controlled study with 2x2 factorial design to evaluate 
1) RfMDA in response to a passively identified index case compared to RACD, and 2) RAVC in 
response to a passively identified index case compared to no RAVC. The advantage of a cluster 
randomized controlled study design is that we are able to assess the impact of a community level/public 
health intervention while controlling for potential confounders that may independently lead to changes 
in health outcomes. The factorial study design is advantageous because it enables evaluation of two 
interventions independently, as well as the evaluation of the combined intervention. Assuming there 
is no interaction between the two interventions (as is hypothesized between RfMDA and RAVC), the 
2x2 factorial study design allows for a smaller sample size (than would normally be used for a three-
arm study) can be used to compare intervention 1 (RfMDA) with control (RACD) and intervention 2 
(RAVC) with control (no RAVC). Specifically, it would require a comparison of 28 EAs, or clusters, 
in each arm to compare RfMDA to RACD, and to compare RAVC to no RAVC. A three-arm study 
would require 78 EAs, but the factorial design allows enables a similar analysis with just 56 EAs. 
Additionally, because the hypothesized effect is greatest in the “combination” cell, we can likely assess 
an effect using only the 14 RfMDA with RAVC EAs versus 14 RACD only EAs. 
Effectiveness to interrupt transmission is the primary outcome of interest for this study. Entomologic 
inoculation rate (EIR) is the gold standard measure of transmission; however, given the low sporozoite 
rates among mosquitoes in low transmission settings such as Namibia, it is an impractical measure for 
this study. Instead, our primary outcome will be the cumulative incidence of confirmed, passively 
detected malaria cases in study EAs, in each arm, over two transmission seasons. Significant time and 
effort has been spent working with the MoHSS during the first phase of the trial to ensure that the 
passive surveillance system is as complete and as close to real-time as possible. While incidence is a 
standard measure captured through health facility reports, it does not capture asymptomatic infections 
in the community. Therefore, we will conduct cross sectional surveys before and toward the end of the 
study, at the end of the transmission season, to measure seroprevalence and infection prevalence. These 
additional measures of transmission were not selected as primary outcome measures because 
seroprevalence is an investigational diagnostic method and prevalence of asexual and sexual stages 
may be too low for comparison with logistically feasible sample sizes.  
An experience from China, targeting household members and neighbours of index cases, suggests that 
80-95% coverage with RfMDA is needed to interrupt transmission.8As rfMDA has not been evaluated 
elsewhere, there is no evidence that high coverage is feasible. Some challenges for high coverage 
include people’s willingness to take medication without knowing their infection status and the time it 
takes for staff to explain the rationale for taking medication. As high coverage is critical for 
effectiveness, but is mainly an implementation challenge, a secondary goal of this study will be to 
determine the feasibility of achieving at least 80% coverage of each of the interventions among 
targeted, eligible people in target areas in each study arm. 
We will evaluate other aspects of feasibility including safety, acceptability, costs, and adherence. We 
will collect serious adverse event data in all arms and compare counts of serious adverse events (SAEs). 
Acceptability of RfMDA vs. RACD, and RAVC vs. no RAVC, will be evaluated through participation 
rate, focus group discussions, interviews with participants and key stakeholders. The costs and relative 
cost-effectiveness of RfMDA vs. RACD will be evaluated by a costing exercise. In order to evaluate 
a strategy that can be feasibly implemented by malaria programmes, medication will be delivered using 
a modified DOT strategy. Ingestion of the first dose of the medication will be directly observed during 
the first visit to the community, and then the subsequent doses will be left with the participant to self-

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administer. Drug adherence will be measured by performing a pill count after selected interventions in 
the RACD and RfMDA arms. 
3.0 Study Aims 
The overall objective of this project is to conduct a critical evaluation of RfMDA vs. RACD and 
RAVC vs. no RAVC as a surveillance and response strategy for malaria elimination.  
The primary aim is to compare the impact of RfMDA versus RACD, and RAVC vs no RAVC on 
incidence of confirmed, passively identified malaria cases. Our hypothesis is that RfMDA will result 
in a 50% lower cumulative incidence compared to RACD and that RAVC will result in a 50% lower 
cumulative incidence compared to standard spraying. In addition, the following secondary aims will 
be addressed: 
Secondary aims 
Effectiveness:  
1) To compare the impact of each intervention package (RfMDA+/- RAVC, RACD +/-RAVC) on the 
following outcomes. Our hypothesis that RfMDA+RAVC will have the largest impact, followed by 
RfMDA - RAVC, followed by RACD + RAVC, and finally RACD - RAVC, on these outcomes: 
a) Incidence, passively detected at health facilities 
b) Prevalence of infection, among all ages, as measured by LAMP 
c) Seroprevalence, among all ages, measured by ELISA 
 
Feasibility: 
1) To compare coverage of each intervention package and determine the feasibility of reaching 80% 
coverage. Our hypothesis is that the 80% coverage is attainable for each intervention arm and for 
RACD, RfMDA, and RAVC individually. 
2) To compare safety of the interventions individually and as packages. Our hypothesis that the risk of 
serious adverse events will not be higher in any one of the arms versus the other arms. 
3) To compare acceptability of the interventions, individually and as packages. We will assess this via 
refusal rates and qualitative assessment. We hypothesize all study intervention will be similarly 
acceptable. 
4) To compare the costs and cost-effectiveness of the intervention packages. We hypothesize that the 
costs per intervention event will not be higher for people receiving RfMDA compared to RACD, 
and may be cost-saving. We also hypothesize that the combination of RfMDA+RAVC will be most 
cost effective.   
5) To measure medication adherence in both RfMDA and RACD. We hypothesize that adherence will 
be at least 80% in both the RfMDA and RACD arms. 
4.0 Study Site 
For Namibia to reach elimination by 2020 it is essential to address malaria where it will be the most 
difficult to eliminate, which includes Zambezi region due to higher incidence, tropical climate, and 
remote location. Zambezi region faces the additional challenge of imported malaria, due to its heavily 
travelled borders with Angola, Zambia, and Botswana, which people cross without the need for official 
documentation.  
In 2015, Zambezi region reported 12,045 malaria cases, and was among the most malarious regions in 
the country. Zambezi region has a population of approximately 98,000; therefore, the region had 
approximately 123 malaria cases per 1,000 residents in 2015. The study area (See Figure 1) is 
comprised of the area of Zambezi region west of the capital, Katima Mulilo. This part of the region 

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Figure 1: Zambezi Region Health Facilities and study area
was chosen as it has significantly more cases than the eastern part of the region each year. The study 
area is specifically comprised of the EAs that make up the catchment areas of 11 health facilities: 
Batubaja Clinic, Chinchimani Clinic, Choi Clinic, Kasheshe Clinic, Kanono Clinic, Linyanti Clinic, 
Masokotwane Clinic, Sachona Clinic, Sangwali Health Centre, Sesheke Clinic, and Sibbinda Health 
Centre. The approximate population of the study area, according to the 2011 census is 35,381. 
Currently, two MoHSS staff 
focus on malaria in Zambezi 
region, a Surveillance Officer, 
and 
a 
Malaria 
Clinical 
Mentor. The Clinical Mentor 
works with health facility staff 
to ensure they are trained 
appropriately 
and 
follow 
MoHSS case management 
guidelines. The Surveillance 
Officer sits at Katima Mulilo 
Hospital with the MoHSS and 
supports the region’s 2929 
health facilities in surveillance 
and 
malaria 
case 
investigation. The MoHSS in 
Katima Mulilo employs Environmental Health staff who coordinate IRS campaigns each year, aiming 
for universal coverage, among other duties. 
During Phase I of the study, beginning in 2014, the project provided support to help ensure the 
surveillance system was robust and captured all passively detected cases. Results have included nurses 
receiving higher marks on malaria diagnosis, treatment, and surveillance in training pre- and post-tests, 
a greater proportion of health facilities reporting their malaria statistics each week, all health facilities 
in the study area now have posters of the malaria treatment algorithm and the differential diagnosis for 
treatment strategy to help with diagnosis of non-malarial fevers. In mid-2015, a rapid reporting system 
was piloted by the project, whereby cases moved to being reported by tablet over the 3G network, 
usually within 24 hours. 
During Phase II of the study this surveillance system will capture confirmed cases identified passively 
at all study health facilities, and those cases will trigger an intervention by the study team in selected 
EAs. If a person presents at Katima hospital or one of the five private health facilities resides in the 
study area, these index cases will also be included in the study.  
Additionally, if feasible, RDTs and/or DBS will be collected from passively detected cases at health 
facilities in other areas of Namibia to better characterize genotypes of locally circulating parasites and 
more accurately characterize samples within the Zambezi region as locally transmitted versus 
imported. Additionally, cases and age-matched controls from an already existing study will be used to 
allow validation of antibody response to a set of Pf antigens that our group has identified as predictors 
of recent infection, unlike current available markers.26 Therefore, once validated, these new markers 
will be used to measure seroresponse in the endline cross sectional survey (Appendices K and L). 
 
5.0 Study design 
5.1 Overview 

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We will evaluate the impact and feasibility of four intervention strategies (RfMDA with RAVC, 
RfMDA only, RACD with RAVC and RACD only) as surveillance and response strategies in the 
communities around passively detected, confirmed index cases using a cluster-randomised trial with a 
2x2 factorial study design. Randomisation will occur at the administrative level of the EA. EAs will 
be pre-assigned to one of four intervention arms (see Figure 2).  
Figure 2 – 2x2 Factorial Design 
RfMDA vs RACD arms 
 
RACD (28 
clusters): 
RfMDA (28 
clusters): 
No RAVC (28 
clusters): 
RACD only (14) 
RfMDA only (14) 
RAVC vs     
no RAVC 
arms 
RAVC (28 
clusters): 
RACD + RAVC 
(14) 
RfMDA + RAVC 
(14) 
 
The assignment of these arms occurred in late 2015, and those assignments were used throughout the 
2016 season. However, after assessing the 2016 data it was observed that one arm had only 1/3 as 
many cases as any of the other three arms. Therefore, the arms were re-randomised, re-assigning 
interventions to the previously selected EAs (see 6.1 Randomisation for more details). 
With each new passively detected, confirmed index case reported from study health facilities, the 
intervention will be implemented in a Target Area of the EA. A Target Area includes the index case 
household and the surrounding households within 500m. At least 25 people will be enrolled in the 
study during each intervention, beginning with the index case household and then enrolling households 
in order of proximity to the index case. If fewer than 25 consenting people live within 500m of the 
index case, all eligible people will be asked to participate. Houses more than 500 m from the index 
case will never be enrolled in the study. Teams will visit each Target Area twice, enrolling as many 
eligible people as possible on each visit. 
 When considering resident eligibility and enrollment in the trial, the inclusion and exclusion criteria 
listed in Table 2 will be used: 
 
 
Table 2. Inclusion and exclusion criteria for interventions 
 
Inclusion criteria 
Exclusion criteria 
Index case (as 
trigger for 
RACD or 
RfMDA)  
● Malaria infection (local, imported, or 
undetermined origin) confirmed at 
study health facility 
● Resides or overnight visitor to a study 
EA 
● Malaria infection identified through active case 
detection 
RACD or 
RfMDA 
intervention 
● Index case resides or has spent the 
night in study EA in past 4 weeks 
● Provides informed consent 
● All non-index cases that reside or 
spent at least one night within 500m 
of the index case in the past 4 weeks 
 
● Index case does not reside in study EA 
● Refusal to participate 
● Household received the intervention within the 
previous five weeks 
● Treatment Exclusion: (but not inclusion in the study): 
Based on assessment by the study nurse, participants 
with complicated malaria or requiring further 
evaluation will be referred to a health facility 
● Houses more than 500 m from the index case 
household will never be enrolled in the study 

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AL 
Administration 
● Consent to take medication 
 
● Pregnancy in the first trimester 
● Previous regular menstruation with no menstruation 
for most recent four weeks 
● Weight < 5 kg 
● Age < 6 months 
● Severe malaria 
● Known AL allergy 
● History of cardiac dysrhythmia  
● Family history of long QT syndrome 
● Regular intake of QT-prolonging medication(s) 
Pill count 
● People who receive any number of 
RACD/RfMDA drug doses 
● Provides informed consent 
● 
People who did not receive RACD/RfMDA drug 
doses 
● 
Refusal to participate 
Reactive Vector 
Control 
● 
Index case resides in study EA 
● 
Head of household or responsible 
person in charge of household 
provides informed consent 
● 
Index household and six closest 
households consent 
● 
Household head refusal to participate (note that 
refusal to participate in RACD or RfMDA is not an 
exclusion criteria for RAVC) 
● 
Received RAVC in the current transmission season  
● 
Household is > 500 m from the index case  
● 
Household sprayed by MoHSS within past 24 hours 
Endline survey 
(early/ mid 
2017) 
● Reside or spent at least one night in 
the EA in the past 4 weeks 
● Refusal to participate 
(Note: lack of participation in RfMDA or RACD is 
not an exclusion criterion) 
 
5.2 Outcome measures 
Table 3. Outcome measures 
Outcomes 
Indicator 
Primary Aim 
Incidence 
The incidence per person year of all RDT or microscopy confirmed local malaria cases 
identified by passive surveillance in study EAs after the first reported case during the 
study period. Does not include additional cases found through RACD.  
Secondary aims  
 
Effectiveness 
 
Exposure 
Seroprevalence to markers of recent exposure using ELISA (endline survey in mid 
2017) in study EAs. 
Infection prevalence 
Prevalence of infection by LAMP in study EAs (endline survey in mid 2017). 
Feasibility 
Coverage 
Proportion of residents and present visitors who complete initial individual procedures 
for the study (finger prick for RDT in RACD arm, initial dose of AL in RfMDA arm, 
receipt of additional IRS in RAVC arm). 
Adherence 
Proportion of people who complete the course of medication among a subset of people 
initiated on treatment in RfMDA and RACD arms that are randomly selected to 
receive modified DOT, as assessed by pill count. 
Prevalence of SAEs  
Number of participants experiencing SAEs deemed possibly, probably, or definitely 
related to study medication or additional IRS, out of the total number of participants 
who received that intervention (RfMDA, RACD, RAVC, the packages of 
interventions). 
Acceptability 
Quantitative assessment (proportion agreeing to participate in RACD, RfMDA, 
and/or RAVC; proportion reporting that they would participate in future interventions 
at endline cross sectional survey) and qualitative assessment. 
Cost 
Cost per index case-level intervention. 
 
 

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6.0 Study procedures 
6.1 Randomisation 
Before year one of the study (February 2016 - December 2016), the study EAs were randomized as 
described below. However, there was an unexpected and significant outbreak of malaria cases during 
2016 and after the completion of the first year of the study it was determined that incidence and case 
investigations in the study arms were significantly unbalanced, and therefore the study arms have been 
re-randomised. The description of both randomization processes are described below. 
 
Year 1 Randomisation 
The study area includes 102 Enumeration Areas (EAs). Of these, 29 were excluded due to incomplete 
geographic data to assign cases to EAs and 17 of 19 were randomly excluded due to no incident cases, 
based on 2012 to 2014 incidence data. The selected 56 study EAs were stratified by incidence in the 
previous transmission seasons and population size and randomly assigned to one of the four study arms 
(Figure 2). The trends in total incident cases from the study EAs are shown in Table 4. Although the 
data for 2014 are only available through May, as the retrospective data collection occurred May – 
August 2014, this timeline corresponds with the end of the transmission season and cases between 
May and December were not anticipated to have much impact on calculations of incidence. In addition, 
geographical reconnaissance was conducted to collect additional data about villages and health facility 
catchment areas. Depending on the results of those surveys, the final list of eligible EAs may change. 
If there are substantial changes the final randomization scheme will be updated. Any changes will be 
submitted for institutional review prior to implementation. The final randomization included 56 EAS, 
allowing for 14 in each of the four study arms. 
Year 2 Randomisation 
For the second year, the same 56 EAS will be re-randomized using a restricted rather than a stratified 
randomization. To guard against unbalanced incidence, we will add additional factors to the restriction 
process. The restriction will include the following criteria:  equal distribution of EAs with 1 or fewer incident 
malaria cases in the 2013 and 2014 transmission seasons, balance in population size, population density, mean 
distance between households, mean distance to a health facility and incidence in the three years with EA level 
data. Due to lack of available data (2015) and concern for an anomalous outbreak year (2016), only the 2013 
and 2014 seasons will be used to balance incidence across study arms. A random set of 100,000 assignments 
will be generated and those meeting the restriction criteria will be selected. The final randomization allocation 
will be chosen from those randomly generated assignments which meet the restriction criteria.   
 
Table 4. Incident, passively detected, confirmed malaria cases in study area (Jan 2012 – May 
2016) 
Year 
2012 
2013 
2014* 
2015 
2016     
(Jan – May 15) 
# Cases 
91 
429 
667 
251 
1,477 
# cases in 
study EAS 
from recent 
data 
196 
361 
452 
? 
603 
 
*Data only available for January through May. 
 
Year 2 Randomisation 
During the analysis of the first year of data from the randomized controlled trial, it was noted that the 
number of incident cases in each arm was significantly unbalanced. While the number of cases in three 
arms were relatively balance, with 182 in the RfMDA only arm, 196 in the RACD only arm, and 164 
in the RACD + RAVC arm, there were only 60 cases in the RfMDA + RAVC arm. To address this 

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imbalance, the Steering Committee agreed to re-randomize the study arms. The same EAs will remain 
part of the study, but the study interventions will be re-randomized amongst them using a restricted 
randomization process, with restrictions based on population density, distance from a health facility, 
and incidence.  
 
6.2 Target Areas 
A Target Area is defined as the index case households and as many of the closest households needed 
to be included to enrol at least 25 people. The houses will be approached in order of their proximity to 
the index case household. Houses more than 500 m from the index case household will never be 
enrolled in the study. This Target Area size was selected based on the RACD data from Engela, 
Namibia, and Swaziland where the mean number of people screened per index case was 24 to 32.  
If a subsequent index case is reported in a Target Area that has already received an intervention, the 
RACD intervention will not be repeated at households that have received the intervention within the 
past five weeks. For the RfMDA arm, the intervention will not be repeated within five weeks or more 
than twice within 12 months. For cases identified during fieldwork, these will be reported through the 
MoHSS reporting system, but will not trigger a new intervention cycle. 
Based on past surveillance data, and the fact that not all index cases will receive an intervention 
(subsequent cases within 5 weeks in households that already received an intervention be excluded), we 
estimate about 235 index cases per study year in our study EAs.  
 
6.3 Community sensitisation and understanding 
Prior to each season of the study, we plan to build awareness, secure commitment, and encourage 
participation from stakeholders at the national, regional, and local levels. We will meet with members 
of the MoHSS in Windhoek and Zambezi region and other stakeholders in the health sector and 
government. Once the appropriate officials have granted approval, we will sensitise health facility staff 
and community health workers, including meeting them at health facilities and distributing information 
sheets (Appendix A).We will work with community health workers and surveillance teams to sensitize 
community members in areas selected for RfMDA and RACD to discuss the study. 
Each intervention EA will be randomly assigned an intervention before the study begins. Sensitisation 
in all EAs will occur before the study begins according to the intervention assigned. The index case 
will be contacted by telephone before the visit, if possible, and asked to notify other members of their 
household and their neighbours. Before the 2016/2017 malaria season the study EAs will be re-
randomized, with the EAs included in the study remaining the same, but shifting which EAs receive 
which intervention to balance study arms. Sensitization about the change in interventions and re-
randomizations will be included in the pre-malaria season sensitization in late 2016. 
6.4 Index case capture and identification 
Index cases will be identified at health facilities within the study area; cases that are confirmed by RDT 
or microscopy will be eligible for inclusion in the study. Per standard surveillance guidelines, the 
health worker completes the Case Investigation Form (Appendix C) and reports the case through the 
rapid reporting system within 24 hours. Index cases will then be invited to participate in the study by 
the nurse, letting them know that not all those invited to participate will be enrolled, since only those 
who live within a study EA will be included. For index cases who agree to be enrolled in the study, 
study procedures that are not already part of standard surveillance include a second finger prick at 
initial presentation to collect a dried blood spot (DBS) for malaria testing and storage of their sample 
for further malaria related research only. Any index case who declines to participate in the study will 
not be enrolled and their RDT will not be saved. For these cases, the MoHSS will then decide whether 
to investigate the case according to standard procedures. 

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After a case is reported through the rapid reporting system, the NVDCP Surveillance Officer and the 
study team may access those data via a secured, cloud-based database. If the case lives in a study EA, 
and has provided consent to participate in the study, a Field Investigator will call the index case, and 
if possible, schedule a visit to the home of the index case. During the household visit, the field 
investigator will double-check the household ID, capture GPS coordinates, and assign a household ID 
if there is not one. If a DBS was not collected at the health facility, if the index case consents (Appendix 
Q), the nurse will collect a DBS. If the implementation of a study intervention is outstanding (e.g. 
delayed reporting, index case unable to be reached), eligibility for enrollment will expire four weeks 
after the case was diagnosed at a study health facility. 
 
6.5 Enrollment of a Target Area for RfMDA or RACD 
When an index case meets the criteria to trigger an intervention, the Target Area around that case will 
be enrolled in the study (see Table 2). If a new index case presents within 5 weeks of when RfMDA 
or RACD was conducted for a previous index case, only households that did not previously receive an 
intervention will be included. 
The study staff will begin recruiting participants from the home of the index case, and then move on 
to neighbouring households in order of proximity to the index case household. The team will attempt 
to enroll at least 25 people per index case, enrolling as many people living within 500m of the index 
case as possible during two visits. At a minimum, the team should continue until the 25th person is 
enrolled, then continue to enroll all remaining consenting members of that household. If the team has 
time, they should continue to enroll more people rather than stopping at the household with the 25th 
person. If less than 25 people live within a 500m radius the team will stop once all eligible, consenting 
residents have been enrolled.  
On the first visit, the team will record the GPS coordinates of the index case household and will 
determine the closest households while in the field. If possible, this will be performed in advance using 
the household ID number assigned to the household during geographical reconnaissance, which is 
associated with a GPS location. The team will attempt to collect a GPS point of all the houses that are 
eligible to participate in the study, both those who participate and those who do not, with the permission 
of household heads (see Appendix D). 
Follow-up visit protocol 
● The team always visits every Target Area twice, enrolling at least 25 people, or all consenting 
people living within 500m, unless 100% of residents within the Target Area are enrolled on 
Day 1. 
● The household where the 25th person lives must have all members enrolled, rather than stopping 
at the 25th person.  
● Teams should not stop at 25 people unless they run out of time, but should continue enrolling 
participants until the second day is over. 
● On the second visit teams must re-visit every household where 100% of residents were not 
given the opportunity to participate in the study, then move on to households that were not 
previously approached, in order of distance from the index case, within 500m. 
 
The goal will be to complete two visits within 14 days of the index case identification date; however, 
visits can be initiated up to four weeks from when the index case was diagnosed. RACD or RfMDA 
interventions not initiated within four weeks, and not completed within eight weeks, will be closed.  
Enrolling members of vulnerable groups 
Vulnerable groups invited to participate in this study include females and children. Their participation 
in this study is critical because they represent high-risk groups for malaria infection. 
Females 
If a female is eligible to receive AL in the RACD arm, i.e. she has a positive malaria test, she will be 
asked (A) if she has ever menstruated, and if yes, (B) whether she has menstruated in the past four 

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weeks. If the answer to A is yes, and the answer to B is no, and she is not in menopause, she will be 
offered a pregnancy test, and if positive she will be excluded from receiving AL. She will also be 
excluded from receiving AL if she refuses to take a pregnancy test. If excluded, she will be referred to 
the nearest health facility for alternative malaria treatment. 
If a female is eligible to receive AL in the RfMDA arm, she will be asked (A) If she has ever 
menstruated, and if yes, (B) whether she has menstruated in the past four weeks. If the answer to A is 
yes, and the answer to B is no, then she will be offered a pregnancy test, and if positive she will be 
excluded from receiving AL. She will also be excluded from receiving AL if she refuses to take a 
pregnancy test. If excluded, she will be tested with an RDT if she consents. If the RDT is negative, no 
further action will be taken, and if it is positive, she will be referred to the nearest health facility for 
alternative malaria treatment. 
Children 
If children are enrolled as index cases or in the community, the consent of a parent or guardian will 
always be sought. In addition, participants who are 12-17 years old will be asked for their assent to 
participate.  
- 
If a child is an index case and the parent/guardian is unavailable at the time of the positive 
RDT, no second finger prick to collect blood for a DBS will be conducted. The child will be 
treated at the time of the visit according to MoHSS protocol. Permission to enroll the child in 
the study will be requested during the community level visit. 
- 
If the child is a resident of a target area and no parent or guardian is available to give consent, 
basic information about the household will be collected, including location, number of 
residents, and household head name. The team will then revisit that household to attempt to 
receive consent from an adult. No person under 18 years old will be given an RDT or treated 
without the consent of a parent or guardian. 
 
 
6.6 Reactive Case Detection (RACD) 
A study team, made up of a field investigator, a driver, and a nurse, will arrive at the household of the 
index case and ask for permission to conduct RACD, checking in with the village headman first if he 
is available. Starting in the home of the index case, informed consent will be requested (see Section 
11.1). If consent is obtained, a short survey will be administered at the household and individual level 
(see Appendices E and F), blood will be collected by finger prick for RDT testing with a CareStart 
RDT (which tests for Plasmodium falciparum and other species of Plasmodium) and a DBS, consisting 
of four spots, will be collected. 
Anyone who tests positive by RDT will be treated by a study nurse on site per national policy with AL 
or with AL+PQ once the new policy has been rolled out. Anyone testing positive that is symptomatic 
and warrants further evaluation will be treated on site and referred to a health facility. Those treated 
will be administered the first dose of AL via DOT, will be informed that someone may return to 
conduct a pill count at the end of their treatment course, and will be instructed to save the drug 
packaging (see Appendix J). Cases detected by RDT in the community during RACD will not become 
new index cases in the study; however, the case will be reported to the MoHSS via the rapid reporting 
system. 
6.7 Reactive focal MDA (rfMDA) 
A study team, made up of a field investigator, a driver, and a nurse, will arrive at the household of the 
newly reported index case and ask for permission to conduct RfMDA, checking in with the village 
headman first, if he is available. Starting in the home of the index case, the study team will ask for 
informed consent from all residents to be treated for malaria, without a malaria test. If consent is 
obtained, the team will proceed with the household and individual level questionnaires.  
For RfMDA, we will use AL, which is currently the first line drug used for uncomplicated malaria in 
Namibia. AL requires two daily doses for three consecutive days, for a total of six doses (see Appendix 

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I). The first dose is followed eight hours later by the second dose. For days two and three, a twice-
daily (morning and evening, 12 hours apart) dosing schedule is adopted. The first antimalarial dose 
will be administered by DOT. Subsequent doses will be left with the participant or guardian, with 
instructions on how to self-administer. Study staff will revisit target areas up to once more to enroll 
more residents. Those treated will be informed that someone may return to conduct a pill count at the 
end of their treatment course and will be instructed to save the drug packaging (see Appendix H). 
AL will be dosed per manufacturer guidelines. The six-dose AL regimen will consist of adult dosages 
for adult patients and AL will be dosed to children according to weight- and age-based guidelines (see 
Appendix I). Participating children under 18 years of age will be weighed at enrollment to determine 
the correct dosage. Participants will be encouraged to take AL with a meal in order to maximize 
absorption, per manufacturer instructions. For infants and children unable to take tablets, drugs will be 
crushed, mixed with 1-2 teaspoons of water or juice and administered as a suspension. As part of the 
informed consent process, participants will be given instructions on what to do in the event of an 
adverse reaction (see Safety Section). The shelf life of AL is 24 months. Expired drugs will not be 
used.   
The administration of AL will follow the Namibian national policy, according to which this agent will 
not be given to participants with: pregnancy in the first trimester, weight less than 5kg, age less than 
6under two months, known AL allergy, severe malaria, personal history of dysrhythmia, concurrent 
usage of QT-prolonging medication(s), or family history of long QT syndrome. In consultation with 
the MoHSS, the principal investigators have compiled a comprehensive list of all QT-prolonging 
medications that are available in the Study Area (Appendix F). Subjects taking any of these 
medications will be excluded from the RfMDA intervention. All females over 10 years of age will be 
asked about menses. Those who have reached menarche but have not menstruated in the past four 
weeks will not be given AL. Individuals who cannot safely be given AL will be tested by RDT during 
the intervention visit. At the time that blood is collected for RDT testing, the same finger prick will be 
used to generate a dried blood spot. Four spots of blood will be collected for each DBS. Participants 
testing positive by RDT will be treated by the study nurse or, if indicated due to symptoms or to AL 
contraindications, referred to the closest health facility for treatment. 
6.9 Reactive vector control 
Half of all study EAs will receive reactive vector control (RAVC) in addition to RACD or RfMDA. 
The spray team will spray seven households in each Target Area in an RAVC EA that are within 500m 
of the index case household. The RAVC team will ask permission to spray each eligible house. Study 
households are eligible to receive RAVC regardless of whether they agree to RACD or RfMDA. The 
team will spray each household with the WHO approved insecticide, micro-encapsulated pirimiphos-
methyl (Actellic® 300 CS). 
On the day of RAVC, the spray personnel will inform household residents of the purpose of spraying 
and will give the household time to prepare and vacate the house. The household members should 
remove all household items, including water, food, cooking utensils and toys from the house. When 
possible furniture should be moved outside, if this is not possible, it should be moved to the middle of 
the room to allow easy access for spraying walls and covered. All wall hangings should be removed. 
When water jars cannot be removed, they should be covered. Pets and domestic animals should be 
tethered away from the house. Occupants must leave houses before spraying and any rooms occupied 
by sick people who cannot be moved will not be sprayed. All walls and the ceilings of all sleeping 
structures used by the household will be sprayed according to NVDCP guidelines at an application rate 
of 40 ml/sq m with a Hudson X-pert sprayer (H D Hudson Manufacturing Company, Chicago, Ill, 
USA). Rooms will not be sprayed if people or animals are present, or if household items are not 
correctly removed or positioned. It is estimated that the RAVC procedure from start to finish will take 

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approximately one hour per residence. 
Household members will be asked to mop up any excess solution from the floors and wash the floors 
with water before they allow young children back into the house. They will be reminded not to wash, 
paint, or re-plaster sprayed walls at least until the end of the malaria transmission season. 
A household that already received RAVC in the current malaria season will not be eligible to be 
sprayed again in that season. At least six months must pass between administrations of RAVC in the 
same structure. At least one week must pass between standard MoHSS IRS and RAVC. 
Those Target Areas not randomized to RAVC will receive no additional IRS, but should have had the 
opportunity to have their household sprayed by the MoHSS during the regular, annual spray season. 
6.10 
Adherence 
In order to evaluate medication adherence, study staff will return to perform a Pill Count for 
participants who were prescribed AL in the RACD arm and a sampling of people given AL in the 
RfMDA arm. There are limited data on the expected adherence to three-day regimen among 
asymptomatic people. Among symptomatic people, the reported adherence ranges from 39% to 
100%.27Due to the return visit by study staff and perceived risk among people residing near an index 
case, we hypothesize that adherence for a complete course of AL will be equal in both arms, and at 
least 80%. The pill count will occur in one Target Area in each study EA, and therefore adherence data 
will be collected in 56 intervention events. 
6.11 
Acceptability 
Acceptability will be assessed using mixed methods to triangulate findings. The quantitative 
assessment will be based on the participation rate in RACD and RfMDA +/- RAVC. We will also 
assess acceptability in the endline cross-sectional survey by asking if residents would be willing to 
participate if offered the intervention again (see Appendix V). The qualitative portion will explore the 
acceptability of RACD compared to RfMDA among participants, refusers, and key stakeholders. A 
pre-intervention qualitative assessment of acceptability was included in Phase I of the study and 
involves focus group discussions (FGDs) to explore acceptability of RfMDA and strategies for 
working with communities to increase the likelihood of acceptance of the interventions. The qualitative 
data collection will continue for the duration of the study. The results of this acceptability study will 
be used to refine the study on an ongoing basis, as well as strategies for malaria elimination in Namibia 
and other malaria-eliminating settings. 
We will use interviews and FGDs to understand participants’ situational perspectives in regards to the 
study.28The importance of using qualitative methods as an adjunct to clinical trials has been 
documented.29Additionally, this approach has been validated, as previous studies have used participant 
and key stakeholder interviews successfully to capture important information regarding community 
acceptability of new treatment modalities.30,31 
 
Focus Group Discussions 
We will conduct FGDs in Target Areas from each arm of the study. The goal of the FGDs is to identify 
barriers to malaria elimination strategies and to identify solutions where possible. We will conduct 
FGDs with participants after a study intervention has occurred. FGDs will be segregated by gender, 
with one FGD with each gender in each selected Target Area. Community leaders will be excluded 
from FGDs, but can be interviewed as key stakeholders to avoid tension. We will conduct 3-5 FGDs 
of approximately 7-12 people in each arm of the trial, continuing beyond that number if saturation has 
not been reached.  
FGDs will explore why community members chose to opt in or out of the intervention(s), possible 
barriers and facilitators to RACD, RfMDA, and RAVC, and positive and negative experiences with 
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All focus group participants will provide verbal informed consent for participation and audio recording 
of the session. FGDs will be held at a convenient location in the area where the intervention took place.  
 
Participant, Refuser, and Key Stakeholder Interviews 
Participant Interviews 
To appreciate the reasons why people accept or refuse to participate in RACD, RfMDA, or RAVC, we 
will conduct semi-structured individual interviews with residents of Target Areas who were invited to 
participate in the study, both those who chose to participate and those who did not. Through a mix of 
open and closed ended questions, we will explore how community members view the interventions 
and why. Interviews will take place in the village where the participant resides or at the local health 
facility. All interviews will be audio-recorded with verbal consent from the participant. We will use 
purposive sampling to identify members of the community who have participated in the clinical trial.  
Refuser Questionnaire 
A short questionnaire will be given to those who refuse testing, treatment, or spraying at the time of 
refusal (see Appendix F). The questionnaire will ask about past participation in malaria screening and 
reasons for refusing participation in this study. These surveys will last approximately 5-10 minutes 
and participation is voluntary. 
Table 5. Acceptability Assessment – Study population, sample size, inclusion and exclusion criteria 
Aim 
Study population and 
sample size 
Inclusion criteria for 
Acceptability Assessment 
Exclusion criteria for the 
Acceptability Assessment 
Key 
stakeholder 
interview 
People who hold leadership 
positions in government or 
health within Zambezi region; 
at least 12 people total. 
● Male and female  
● In a leadership position in 
Zambezi region 
● Provide informed consent 
● Refusal to participate 
● Not in a leadership position 
Refuser 
interviews 
Everyone refusing RfMDA, 
RACD, or RAVC. If an entire 
household refuses, household 
head will complete. 
● Refuses to participate in 
RfMDA, RACD or RAVC 
● Agrees to a short 
anonymous survey  
● Refusal to complete refuser 
survey 
● Age under 15 years 
Focus 
group 
discussions 
with study 
participants 
Anyone who was eligible to 
be enrolled in the study 
within that Target Area. 
3 – 5 FGDs in each arm of the 
trial. 12 – 16 total FGDs, 84 – 
160 people, half with women, 
and half with men. 
● Male and female 
participants and refusers 
● Residents of selected Target 
Area 
● Provide informed consent 
● 
Refusal to participate 
● 
Key stakeholder or in other 
leadership position 
● 
Age under 15 years 
Quantitativ
e 
assessment 
Participants in the study 
intervention and 2017 cross 
sectional survey. Both 
participants and non-
participants in interventions. 
● Invited to participate in 
study intervention, 
participating in the endline 
cross-sectional survey 
● Refusal to participate in 
cross-sectional survey 
 
 
Key Stakeholder Interviews 
During the trial, key stakeholders will interact with the community members to facilitate the trial. 
Local stakeholders, including members of local, district, and regional leadership and health facility 
and community health workers, will be engaged through key stakeholder interviews. These interviews 
will explore the role of the key stakeholder in the clinical trial, experience with malaria elimination in 
Namibia, acceptability of RACD, RfMDA, and RAVC as strategies in their communities, and reasons 
community members agree or disagree to receive testing and/or treatment.   
Key stakeholder interviews will last approximately 45 minutes. We will interview at least 12 key 
stakeholders including two from each constituency involved in the study (Judea, Kongola, Linyanti, 

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and Sibbinda) as well four people within regional government and health leadership. When considering 
eligibility and enrollment in the acceptability assessment, the inclusion and exclusion criteria listed in 
Table 5 will be used. 
6.12 
Costing study 
The goal of the costing study is to compare cost per intervention event in RfMDA versus RACD +/- 
RAVC. Our hypothesis is that the costs of RfMDA per intervention event will be lower than RACD 
due to the cost and personnel timesavings from not performing a diagnostic test. Of note, if RfMDA 
is more effective, cost per index case may be higher in the RfMDA arm due to decreasing incidence; 
however, if RfMDA is more effective, the cost per case averted (compared to RACD) may be lower. 
We will collect detailed expenditure data on costs of delivery of RfMDA, RACD, and RAVC 
interventions. We will collect total costs (including costs for all consumables, as well as staff time) for 
RAVC to give the MoHSS an estimate of total cost and feasibility of implementation. 
6.13 
Drug Potency Study 
A sample of the study drug will be pre-identified and transported on field visits throughout the trial. 
At the end of the trial, the sample will be tested for potency. This is designed to reconcile manufacturer 
instructions that warn against storage above 30<0000>C because temperatures in the study area are regularly 
above this threshold. 
6.14 
Serology validation sub-study 
The purpose of this sub-study is to validate putative markers of recent malaria exposure, which will be 
used in the endline survey (see Section 6.15). This sub-study will enroll approximately 300 individuals: 
100 RDT-positive and LAMP or PCR-confirmed cases as well as 200 age- and gender-matched, RDT, 
LAMP, and PCR-negative controls). These cases and controls will be randomly selected from the 
Phase I case control study and Phase I cross-sectional survey study participants. Enrollment in the 
serology validation sub-study will consist of two additional visits and will begin approximately 6-12 
months after cases and controls were initially identified by RDT in the corresponding Phase I study. 
For the first serology sub-study visit, staff will contact the previous study participants by phone, and 
then visit them at their homes. After new consent is obtained, a short questionnaire regarding malaria 
risk factors will be administered, an RDT will be performed, a DBS containing four spots, and a 180 
<0000>L whole blood sample in a microtainer will be collected. Samples from each of the two sub-study 
visits will be labelled with a barcode encoding a unique alphanumeric serology sub-study identifier. 
Study staff will return for up to two additional visits per participant per time point to ensure high 
capture. 
For the second and final serology sub-study visit, the above procedure will be replicated 6-12 months 
after the first sub-study visit. Informed consent will be collected at each sub-study visit. 
Analysis of these samples will refine our current knowledge of serologic markers of recent (within 9 
months) versus remote (greater than 24 months in the past) malaria exposure in low endemic settings. 
The antibody markers we identify as having the highest degree of association with the first and not 
with the second time point, will be used in the post-intervention endline survey to measure 
seroprevalence. More broadly, this serologic information will help inform future tools used in Namibia 
to measure exposure and to document interruption of transmission.  
6.15 
Endline Survey 
A follow-up blood survey and questionnaire will be conducted toward the end of the study in early/mid 
2017. A sample of residents, representative of the four study arms, will be requested to participate. 
After informed consent is obtained, a short household and individual questionnaire will be 
administered. A finger prick will be performed to collect blood for a CareStart RDT, to test a new 
highly sensitive RDT, and to collect a DBS as well as ~300 microliters of whole blood in a microtainer. 
Approximately 25 households will be enrolled in each of the 56 study EAs, for approximately 5,040 
people. The 25 households will be randomly selected from among all households in that EA. Residents 
who did not participate in the intervention are eligible for participation as the goal of the study is to 

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evaluate community level impact. Study staff will return for up to one additional visit to ensure high 
capture. 
The main purpose of the endline survey is to perform measure prevalence of malaria infection. The 
endline survey will also collect blood samples to perform serological assessments looking at markers 
of recent exposure will enable comparisons of recent transmission between the two arms, and thus 
impact of RACD vs. RFMDA +/- RAVC. A serological assessment looking at markers of past 
exposure will enable comparisons of baseline exposure between the two arms. These samples will also 
be used to measure infection prevalence using quantitative PCR.  
A secondary purpose of the endline survey is to measure the diagnostic accuracy of a new highly 
sensitive RDT (HS RDT) which can detect the presence of Pf and is predicted to be ten times more 
sensitive than current RDTs. The HS RDT will be run by nurses in the field in parallel to the Carestart 
RDT and the proportion of participants positive by HS RDT will be compared to the proportion 
positive by quantitative PCR and quantitative HRP II assay (HRP II is the HS RDT’s analyse) to 
determine the sensitivity, specificity, positive predictive value and negative predictive value of the HS 
RDT. 
7.0 
Safety and Risks 
The safety risks associated with participation in this trial are expected to be minimal. The study drug, 
AL, is well tolerated. Prior to AL administration, participants will be asked about known allergy, past 
adverse reactions felt to be associated with the medication, and other contraindications (see Table 2). 
Participants will be restricted from taking the medication if such a history is reported. Participants who 
test positive during our study but cannot safely receive AL will be referred to the nearest health facility 
to receive an alternate antimalarial medication per MoHSS policy.  
For RDT positive cases found to have uncomplicated Pf infection, single dose PQ may be additionally 
administered if the MoHSS national policy endorsing this intervention is initiated during the time 
period of our study.32 Pregnant women and infants under one year of age will be excluded from PQ. 
Monitoring of serious adverse events (SAEs) potentially related to AL or Actellic CS will occur 
passively and actively (see Sections 7.2 and 7.3). Participants will be instructed to seek care at their 
local health facility or to call the on-call Study Nurse if they experience any adverse reactions while 
or after taking AL or after IRS with Actellic. When any adverse event is reported, a study nurse will 
complete an adverse event reporting form. 
During the pill count, the study nurse will ask participants about possible toxicities, with any 
affirmative answer triggering the completion of an adverse event reporting form. All serious adverse 
events will be reviewed by the study nurse within 48 hours of notification, who will then discuss the 
event with the study physician (see Section 7.1). The study physician will assess causality by collecting 
additional data on the relationship between the drug and the event and will recommend whether the 
participant remain in or be withdrawn from the study, advising the study nurse and/or health facility 
worker accordingly. For each SAE, a separate SAE form will be completed (see Appendix N).  
 
7.1 Passive identification of SAEs 
Prior to the start of the trial, a training took place at each of the 11 study health facilities to educate 
health facility staff on adverse event reporting procedures and forms, and to share the phone number 
of the on-call Study Nurse. For adverse events detected at the health facilities, health facility workers 
have been trained to notify the Study Nurse immediately. The Study Nurse will be available 24 hours 
per day, seven days per week on a mobile phone reserved for this purpose. The Study Nurse will 
investigate each adverse event within 48 hours of notification, collecting pertinent information, 
classifying severity (see Appendix M), and filing the report. For all SAEs, the Study Nurse will discuss 
management with the Study Physician, who will advise whether the participant should continue or stop 
treatment due to safety concerns. Study personnel will assist with referrals to the local hospital, if 

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indicated by the Study Physician. For less serious symptoms, the Study Nurse will advise health facility 
staff on management. 
Participants will be given the telephone number of the on-call Study Nurse and may report adverse 
events directly. Management of such events will follow the same guidelines, with SAEs being 
mandatorily discussed between the Study Nurse and Study Physician, and with lesser severity AEs 
being managed by the Study Nurse directly (with added input from Study Physician at the discretion 
of Study Nurse). 
For each adverse event, the Study Nurse will arrange a follow-up visit within 72 hours at a convenient 
location (at home, school, or if indicated a health care facility). If this is in response to a SAE, the visit 
will include the Study Physician. Subsequent follow-ups of the adverse event will continue until 
resolution is documented. 
7.3 Active identification of SAEs 
During the pill count (see Section 6.10), participants given AL in the RACD arm and to a randomly 
selected subset of participants in the RfMDA arm, study staff will ask participants about possible 
toxicities from the study medication. This inquiry (see Appendix H) will utilize an open-ended method 
to assess for side effects and includes documentation of what immediate measures were taken by study 
staff members to alleviate an adverse reaction. Any affirmative answer will trigger the completion of 
an adverse event reporting form.  
7.4 Expedited reporting of SAEs and SUSARs 
The Study Physician will report each SAE and serious unexpected serious adverse reactions (SUSAR) 
to the management team immediately. After management and PI review, the information will be 
transmitted to the Data and Safety Monitoring Board (DSMB) within one week of occurrence and will 
be reported to the MoHSS Therapeutics Information and Pharmacovigilance Centre in parallel (Room 
21, Basement Area of Windhoek Central Hospital, Tel 061 203 2312, Fax 061 22 66 31/ 088 618 776, 
info@tipc.com.na). Reports of SAEs that are classified as possibly, probably, or definitely related to 
study intervention, and reports of all SUSARs will be submitted to the IRBs at UCSF, UNAM, 
MoHSS, and LSHTM, within 7-10 days of occurrence, per corresponding IRB stipulation. 
7.5 Management of participants with SAEs 
If a study participant experiences an SAE classified as related to a study drug, decisions on whether 
the participant should complete treatment or stop will be made by the health facility worker providing 
treatment at the health center in consultation with the Study Physician. If the participant does not report 
to a health facility, this decision will be made by the Study Physician in consultation with the Study 
Nurse. Factors that will be considered will include the type and severity of the event and suspected 
strength of the association between drug and the event (possibly, probably, or definitely related). In all 
cases, the potential risks and benefits will be weighed and decisions will be guided by the best interest 
of the patient. The Study Physician will investigate to assess associations and severity, and will follow 
up with cases to ensure resolution. The Study Physician may consult with his or her physician 
colleagues to review associations and severity. 
 
7.6 Adverse event monitoring - Data and Safety Monitoring Committee 
A DSMB will be assembled, consisting of at least four members who are independent of the project 
and who have not contributed significantly to the project’s design. Members will include experts in 
statistics, epidemiology, clinical trial design, and a clinician. The DSMB will elect a Chair and a 
Secretary. Depending on the agenda, independent advisors or experts can be invited to the meeting, 
upon approval by the chair and secretary. The DSMB, principal investigators, and sponsors will agree 
on the rules for reporting safety data during the course of the project, frequency of formal meetings 
(likely quarterly), and the rules for recommending premature termination of the project on grounds of 

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safety or endpoint futility. The DSMB will review the study protocol and analytical plan prior to the 
onset of the study and will review SAE and SUSAR reports during the trial. After immediate 
management by the Study Physician, final decisions regarding continuation of study participation for 
participants experiencing SAEs causally related to AL will be made by members of the DSMB. See 
Appendix P for the DSMB Terms of Reference.  
Meetings 
The committee will meet at regular agreed-upon intervals, likely quarterly, and as needed if safety 
concerns necessitate. DSMB members are expected to attend meetings in-person or by teleconference, 
and should not rely upon substitute representatives. Members will participate in email discussions as 
necessary, and will be updated regularly on RfMDA progress and activities.  
Stopping guidelines 
The DSMB members will make decisions about discontinuation of the study. Stopping guidelines will 
be based on the prevalence of serious adverse events deemed to have a causal association with the 
study intervention as well as based on enrollment and consequent likelihood of endpoint assessability. 
 
7.7 Potential risks and discomforts 
Randomisation 
In this cluster-randomized trial, participating EAs will be randomly assigned to one of four intervention 
arms (RACD +/- RAVC, or RfMDA +/- RAVC). One intervention may prove to be more or less 
efficacious, more or less well-tolerated, and/or more or less safe than the standard of care (RACD 
alone). Thus, there is the risk that EAs will be randomized to a less efficacious, less well-tolerated, 
and/or less safe study arm. However, such risks associated with randomization in this study are likely 
to be low.   
Artemether-Lumefantrine 
Artemether-lumefantrine has an excellent efficacy and safety profile and is the first-line treatment for 
uncomplicated malaria in 23 African countries, including in Namibia. Side effects that have been 
described in recipients of AL include headache, dizziness, loss of appetite, generalized weakness, 
fever, chills, fatigue, arthralgia, myalgia, nausea, vomiting, and abdominal pain. We will monitor for 
AEs and SAEs during this trial. 
In general, ACTs, such as AL, are not recommended for use in the first trimester of pregnancy due to 
insufficient safety data regarding teratogenicity. To minimize any safety risks associated with AL 
treatment, we will not offer this agent to women in their first trimester or to postmenarchal, pre-
menopausal women who have experienced no menses in the past four weeks. Due to limited data in 
infants under 5 kg, these participants will not be administered AL either. In accordance with Namibia’s 
national malaria policy, infants under 6 months of age will not receive AL, nor will patients with 
severe/complicated malaria receive AL. Participants who have tested positive by RDT and who, based 
on the exclusions above, cannot be given AL safely, will be referred to the nearest health facility, 
where they can be evaluated to receive an alternate MoHSS-approved agent. 
RAVC using Actellic CS 
Actellic CS has an excellent human and environmental safety profile. The spray presents no significant 
risk to spray operators, household members, or the environment, when used correctly. It is possible 
that insecticide left unattended could be accidentally ingested by a child. To prevent such an event, 
spray operators will not leave insecticide unattended or unlocked in their vehicle. Study personnel who 
will directly be handling Actellic CS will attend MoHSS spray trainings in order to be educated on 
proper safety measures. 

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Blood draws 
The potential risks of drawing blood from a finger-prick include temporary discomfort, pain, transient 
bleeding, bruising, skin infection, and fainting. The volumes of blood taken will be too small to 
produce any adverse physiologic effects from blood loss anemia and overall the aforementioned risks 
associated with blood draws are likely to be low. Study staff will be trained in the proper conduct of a 
finger-prick according to standard operating procedures to minimize the risk of discomfort and 
infection.  
Positive malaria tests 
In the RACD arm and the serology sub-study, RDT will be provided to each participant. 
Complimentary treatment will be offered if the RDT result is positive, provided the participant does 
not have signs of complicated/severe malaria and has no contraindications to AL. Participants with 
positive tests will be told to seek care at the health facility if their illness worsens. It is possible that 
for some cases in the community, the RDT will be negative, but the subsequent molecular (PCR or 
LAMP) test will be positive. This most commonly occurs when parasitaemia is below the level of 
detection for RDTs, but not below the level for LAMP or PCR. These participants will not be treated, 
as performance of LAMP or PCR is for research purposes. The risk of developing symptomatic or 
severe illness is very low from a presumably low parasitaemia in an RDT-negative asymptomatic 
individual. Of note, RDTs are used nationally at the point of care in health facilities, with treatment 
based on the result of the RDT and not on a confirmatory molecular test. 
Confidentiality 
The risks associated with loss of privacy in this study are likely to be low. To ensure confidentiality is 
maintained, all information will be treated as private by study personnel, and records kept securely in 
locked filing cabinets and offices. Electronic records will be kept on a secure, firewall- and password-
protected server. For all data collected as part of the study, participants will be assigned a unique 
identification number. No personal identification information such as names will be used in any reports 
arising out of this research. All project staff will be trained on procedures for maintaining 
confidentiality. Study staff will routinely discuss what other measures can be taken to minimize risk 
as issues arise during the study.  
Compensation 
Participants will not be paid to take part in this study. Most assessments will be conducted at 
households, which will eliminate the need for participant travel and minimize opportunity costs for the 
participants. Any diagnosis and treatment associated with the study will be provided free of charge. 
8.0 
Laboratory procedures 
The laboratory procedures described below will be followed for all laboratory-based activities 
conducted during this project. The laboratories performing these tests include the UNAM campus in 
Windhoek and Katima Mulilo and UCSF. LAMP, PCR, and possibly ELISA, will be conducted by 
UNAM. Parasite genotyping, and possibly ELISA, will be performed at UCSF. Parasite species 
identification with PCR will be performed at either UNAM or UCSF. 
8.1 Rapid diagnostic tests 
Carestart RDTs will be used in the field to determine malaria infection status, and will be performed 
on participants every time a blood sample is collected. These RDTs can detect whether Pf infection is 
present or absent, and whether any Plasmodia, including Pf, is present or absent. RDTs will be 
performed according to the directions provided, using the blood transfer device and reagent provided 
by the manufacturer. Nurses associated with the project will perform tests and results will be available 
within 20 minutes. The results will be provided to the participant or their parent/guardian verbally and 
will be recorded. Symptomatic and asymptomatic participants who test positive for malaria will be 
treated on site by a study nurse. 

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During the cross-sectional endline survey only, we will test the diagnostic accuracy of a new highly 
sensitive RDT (HS RDT), which can detect whether Pf infection is present or not and is estimated to 
be ten times more sensitive than current RDTs. Study nurses will use a finger prick blood sample to 
run the Carestart and HS RDTs in parallel, according to the manufacturer's instructions. Results will 
be available within 20 minutes and will be recorded by study staff. Participants in the endline survey 
will be treated according to the results of the Carestart RDT since the HS RDT is in the prototype 
phase and is not licensed for use by the WHO. 
 
8.2 Filter paper sample collection 
Blood spots will be collected onto filter paper for future molecular studies for research purposes only. 
Filter paper (Whatman 3MM) will be pre-cut into individual squares and stapled to a thick card that 
will serve as its cover. Blood spots will be collected onto the filter paper in volumes of approximately 
25 µl aliquots per blood spot (4 blood spots per card). Filter paper samples labelled with the 
individual’s barcodes or ID number on the covering cardboard, and will be allowed to dry at ambient 
temperature and relative humidity before closing the card over the filter paper (like closing a 
matchbook). Filter paper samples will be transported from the field in a Ziploc bag then placed in a 
stock card filter paper box with desiccant and humidity indicator card and stored in a freezer in 
Zambezi region until they are transported to the lab at UNAM in Windhoek where they will be stored 
at -20<0000>C.  
8.3 Molecular Testing 
Dried blood spots will be extracted using the Chelex method with Tween. Whole blood samples will 
first be centrifuged to remove and save plasma. Samples will first undergo LAMP testing using the 
LAMP PAN detection kit, followed by testing with the Pf detection kit if PAN positive. All RDT or 
LAMP positive samples and 10% of negative samples will undergo nested cytochrome B PCR testing 
with species specific identification using a restriction digest.33 Other molecular studies may include 
quantitative PCR, as well as analyses of polymorphisms in parasite and/or human genes for mutations 
that may affect clinical malaria and genotyping of malaria parasites. Molecular studies will be 
performed only for malaria research purposes and will have no impact on the clinical management of 
study participants.  
8.4 Genotyping 
Genotyping of P. falciparum will consist of a panel of microsatellites and/or single nucleotide 
polymorphisms (SNPs) located throughout the genome. Briefly, DNA samples will be amplified in a 
multiplex pre-amplification step followed by amplification of microsatellites in individual reactions 
using fluorescently labeled primers, and sized using denaturing capillary electrophoresis. Multilocus 
genotypes from mixed infections will be reconstructed, where possible, by quantifying alleles at each 
locus. Genotyping of additional loci, potentially including SNPs and/or targeted deep sequencing, will 
be performed as needed. Genotyping will be performed only for research purposes and will have no 
impact on the clinical management of study participants.  
8.5 ELISA 
Serology will be used to measure anti-malarial antibodies for the serology validation study and to 
measure impact of the trial interventions. Serology will also be used to measure levels of parasite HRP 
II antigen from whole blood as part of the endline survey for the HS RDT evaluation since the HS 
RDT detects HRP II in whole blood to determine P. falciparum infection status. Using dried blood 
spots and serum from whole blood, ELISA assays for antibodies will be performed using previously 
described methods.6Briefly, antibodies will be eluted from DBS and assayed to detect antibodies 
against the Pf blood stage antigens merozoite surface protein-1 (MSP-142) and apical membrane 
antigen-1 (AMA-1), both biomarkers of Pf exposure. Other antigens that are sensitive and specific for 
recent exposure that are undergoing evaluation will also be used. ELISA assays will be performed in 
duplicate and optical densities recorded. Other serologic platforms, including bead array and protein 

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microarray, may be used to analyze responses to multiple antigens if available. ELISAs will be 
performed only for research purposes and will have no impact on the clinical management of study 
participants.  
8.6 Sample storage for future studies 
DBS, plasma, and extracted DNA will be maintained at -20<0000>C. After the study period, blood samples 
will be stored for future malaria studies. Consent forms include a statement about future testing. 
Samples will be stored for 25 years, so that if there are new cases after elimination, past samples are 
available for genotyping purposes, as recommended by WHO.34 Comparing new strains to past strains 
will help distinguish between imported and local infection. Re-emergence of new cases could occur 
more than 20 years after elimination as shown by North and South Korea, which eliminated malaria in 
the 1970s, but then experienced a re-emergence in the 1990s. 
9.0 Entomological management 
As vector numbers are expected to be low, this study will not include entomological outcome 
measures. However, since one of the interventions consists of vector control, it will be necessary to 
monitor (1) vector susceptibility to insecticides; (2) species composition; and (3) spray quality on 
walls. 
9.1 WHO insecticide resistance testing 
Susceptibility of the vector population to the four classes of insecticide will be performed at baseline 
and during the final year of the study in each of the four study arms. Adult Anopheles, reared from 
larvae and the F-1 progeny of wild females, will be tested using standard WHO susceptibility tests.23 
Mosquitoes will be exposed to impregnated filter paper discriminating dosages of deltamethrin 
(0.05%), DDT (4%), bendiocarb (0.1%) and Pirimiphos Methyl (0.25%). Percentage mortality and 
median time to knockdown will be measured. If insufficient mosquitoes are available, exposure to 
Pirimiphos Methyl will be prioritized, followed by exposures to DTT, deltamethrin, and bendiocarb 
(in that order). 
If sufficient mosquitoes are found and if there is evidence of resistance, samples will be exposed to 
different concentrations of insecticide on filter paper and mortality will be assessed 24 hours post-
exposure to obtain LC50 data, or exposed to the standard WHO diagnostic dose for varying lengths of 
time to estimate LT50s. All specimens will be identified to species level.  
 
9.2 Mosquito identification 
Mosquitoes will be identified by microscopy and the numbers of identified species recorded. Funds 
permitting, An. Gambiae complex and the An. Funestus group will be identified by PCR. 24 
 
9.3 Spray Quality 
WHO cone bioassays will be conducted on a sample of walls within one month of spraying, using 
insectary reared susceptible mosquitoes. 
10.0 Data management 
10.1 
Quality assurance and quality control 
All study personnel will be trained in the project objectives, methods of effective communication with 
study participants, collection of high quality data, and principles of ethical research practice. Study 
personnel will receive additional training specific to the tasks they will perform within the project, 
including interviewing techniques, administration of surveys, completing questionnaires, and use of 
tablet devices. Standard Operating Procedures (SOPs) will be written for all project activities and 
booklets of all relevant documents provided to each member of the project team. Weekly meetings 

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will be held by the Site Manager to assess progress of the study, address any difficulties, and provide 
performance feedback to the members of the study group. Any corrections to data collection forms 
will be made by striking through the incorrect entry with a single line and entering the correct 
information adjacent to it, according to Good Clinical Practice guidelines. The correction will be 
initialed and dated by the study personnel member. 
10.2 
Records & storage 
The study staff will maintain appropriate medical and research records for this study in compliance 
with the principles of Good Clinical Practice and regulatory and institutional requirements and in 
compliance of the requirements for the protection of confidentiality of participants. Only study 
personnel members will have access to these records. All forms with participant names will be kept in 
a locked cabinet or office when not in use, and the key kept by the Site Manager. All information 
coming from health facilities and data collected during field activities will contain patient/participant 
names. These names are crucial for follow-up. However, when data are shared outside of the Senior 
Management Team, participants will be identified only by their study ID number. All information will 
be stored in HIPAA compliant cloud-based databases, maintained by UCSF, UNAM, or the MoHSS. 
Once the study is complete, all data will be de-identified, with household and individual study 
identification codes remaining to link questionnaires to samples. Data will be stored for at least 5 years 
in secure databases. Authorized representatives of the sponsor, the ethics committees, or regulatory 
bodies may inspect all documents and records required to be maintained by the principal investigators. 
The principal investigators will allow all requested monitoring visits, audits, or reviews. 
11.0 Statistical considerations 
11.1 
Overall study area sample 
Based on 2011 census data and the estimated growth rate of the population, the overall population in 
the catchment areas of the 11 study health facilities is approximately 35,381 people. From January 
2012 to May 2014, 19 of the 102 EAs had no recorded cases, and an additional 29 had insufficient 
geographic data to assign cases. In the selected available sample, EAs vary in population size from 
100 to 583 persons, the arithmetic mean number of people per EA of 300. Because the population size 
of the EAs varied, we used the harmonic mean population size in the selected EAs (267 people per 
EA) in calculations of detectable differences. EAs will be randomized to one of four arms, with a 
minimum of 14 in each arm (56 total EAs). In 2016, there was an unexpected outbreak of malaria, and 
staffing was not sufficient to investigate all cases that presented with incident malaria. At the end of 
2016, we determined that investigated cases were not balanced between study arms, and that protocol 
had not been followed as intended. We therefore decided to re-randomize the existing study EAs and 
re-launch the study. The revised restricted randomization approach is discussed in Randomisation 
section above. EAs will be randomized to one of four arms, with 14 EAs in each arm (56 total EAs).  
11.1.1 Sample size for the interventions 
As defined above, a Target Area is defined as all people living in the six households closest to an index 
case detected via passive surveillance and who resides in a study EA. People who live up to 500m 
from the index case may be included if a minimum of 25 people have not been enrolled in the study 
within the first six households.  
For the 2015-2016 malaria season, estimates on the samples size for the interventions were based on 
2013 – 2014 annual incidence data.  At the time, actual population was calculated at 16,200. To 
compensate for the uneven size of EAs, the harmonic mean of cluster size (267 per EA) was used to 
calculated the effective sample size of 13,884. Incidence was calculated at 19.5/1000 and assuming 
50% decrease due to RFMDA, and 50% due to RAVC, we anticipated 117 index cases during the first 
year of the study, and enrollment of 2925 participants for the study intervention (25 per index case). 
Due to a delayed study launch and limited staffing, we enrolled 1501 participants in the first year of 
the study. 

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For the second year of the study (2016-2017), the expected sample size for the interventions has been 
updated based on measured incidence during the 2015-2016 malaria season and updated figures for 
the population (based on updated estimates from the geographical reconnaissance survey). The 
population has been re-estimated at 18,022 people residing in the study enumeration areas (EAs). 
Using the harmonic mean size of EAs (276 per EA), the effective sample size is 15,456.  Using the 
same assumptions regarding the effectiveness of RfMDA and RAVC, we anticipate 206 index cases 
in the second year of the study. With 25 people/index case receiving the intervention, we expect 5150 
encounters. Based on preliminary RACD data, we anticipate 10% of encounters will occur in people 
who previously received an intervention during the study period (repeated or overlapping Target 
Areas), resulting in 4,635 unique people. If 5% of people refuse an intervention, the total estimated 
number of people we will consent and screen for the second year of the study is 4403.  Considering 
the number enrolled in year one (1501) the total enrollment for the 2 years of the study is expected to 
be 5904.  
 
 
 
 
Table 6 Incidence and effective sample size estimates for year 2 
  
Pre- 
intervention 
RACD no 
RAVC 
RACD plus 
RAVC 
RfMDA no  
RAVC 
RfMDA plus 
RAVC  
Total all study 
arms 
 
Number of EAs 
56 
14 
14 
14 
14 
56 
Incidence 
33.45 
25.09 
12.54 
12.54 
3.14 
13.33 
Effective population 
(based on Hayes 
Moulton) 
15456 
3864 
3864 
3864 
3864 
15456 
Incident cases per year 
517 
97 
48 
48 
12 
206 
Potential participants 
encountered  (25 per 
index case) for study 
year 2 
-- 
2423 
1212 
1212 
303 
5150 
Unique people expected 
to be enrolled for study 
year 2 
-- 
2181 
1091 
1091 
273 
4635 
*Estimated index cases and enrollment updated per 2015-2016 incidence for second year of study.  
 
11.2 
Power to detect differences in primary outcome –Incidence of new infections 
Our primary study outcome is the incidence of passively detected, confirmed local malaria infections 
in the overall population of the EAs randomized to 1) RfMDA vs. RACD and 2) RAVC vs no 
RAVC. Incidence during the 2015-2016 transmission season in the study areas was 33.45 malaria 
cases per 1000 persons per year. To estimate power to detect differences in incidence we used a 
sample size of 56 EAs with an estimated harmonic mean of 276 people per EA (total effective 
sample size of 15,456) for the overall sample. This is a conservative estimate, using a sample size 
lower than the total population (estimated 18,022) to account for the effects of clustering in 
unequally sized clusters and 14 EAs per study arm. The coefficient of variation for incidence among 
the study EAs has been below 0.95 in each of the previous seasons and we used 0.95 as the estimated 
coefficient of variation. We hypothesize that introduction of RACD (which has not been consistently 
implemented in these areas) will decrease incidence to 25.09 per 1000 per year. As there is no 
available data to suggest that RACD using RDTs is an effective method to decrease transmission, it 
is possible that the incidence will not decline. However, this will not have a negative impact on our 
study, as it would only improve our power to detect a difference between the study intervention and 
control. Both trial interventions are hypothesized to reduce the incidence in the study population. We 

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assumed an effect of 50% reduction (rate ratio 0.5) for both RfMDA compared to RACD and RAVC 
vs no RAVC. We further assumed a multiplicative effect of the two interventions combined, or a rate 
ratio of 0.25. Using these assumptions and the sample size as described above we would have 80% 
power to detect an effect of RAVC vs no RAVC and 80% power to detect an effect of RfMDA vs 
RACD and 80% power to detect the hypothesized difference between the combinations of RfMDA 
and RAVC vs RACD with no RAVC. We used the equations suggested by Hayes and Moulton to 
calculate the detectable differences with our sample size.35 
 
 
11.3 
Secondary outcome on effectiveness - Seroprevalence 
In mid-2017, a cross sectional survey with a cluster sampled design will be used to measure 
seroprevalence. Within each EA, 25 households will be randomly sampled. With an estimated 
household size of 4.5 and 80% coverage of selected people, we expect to sample 6,300 individuals and 
enroll 5,040 across the 56 EAs. Based on preliminary data from another similar setting, we expect 
seroprevalence in the RACD arm to be approximately 10%.6 
Accounting for the clustering of cases and assuming 10% seroprevalence in the RACD arm, with a 
sample size of 2,520 in the RfMDA arm and 2,520 in the RACD arm, the endline cross-sectional 
survey will have 80% power to detect a minimum detectable decrease in seroprevalence to 5.3% in the 
RfMDA arm representing a 47% reduction in seroprevalence. 
11.4 
Secondary outcome on feasibility - Coverage 
For this study, coverage for each intervention is defined as follows: 
- 
Investigation coverage – Proportion of eligible cases investigated out of eligible cases reported 
in the Rapid Reporting System 
- 
Intervention coverage (Both RfMDA/RACD) – Proportion of eligible participants enrolled per 
intervention (up to 25 per intervention) out of the number of eligible residents within 500 
meters of the index cases household (up to 25 per intervention) 
- 
RfMDA – Proportion of people eligible for the intervention who took the first dose of AL (up 
to 25 per intervention) out of the number of eligible residents within 500 meters of index case 
household (up to 25 per intervention) 
- 
RAVC – proportion of households receiving spraying (up to seven per intervention) out of the 
number of households within 500 meters of the index case (up to seven per intervention) 
- 
Index case coverage – proportion of eligible participants receiving intervention in the index 
household out of the number of eligible residents of the index household.  
 
People eligible for all arms of the study include all people who live in one of the households closest to 
the index household, or who are recorded as having stayed overnight there at least one night in the past 
four weeks and are present during the intervention. If the intervention team goes beyond the closest 
six households from the index case, residents of all houses approached to be part of the intervention 
will be included in the “eligible population” and will become part of the denominator. Households 
may be approached up to 500m from the index case household, if two visits have been made, all 
households within 500m approached and 25 people have not been enrolled, then the intervention is 
finished. 
Total population of Target Areas will be based on total population recorded during the 2014-2015 
geographical reconnaissance. 
For the feasibility outcome measure of coverage, the goal coverage of 80% for the different 
interventions is based on modelling data and experience from settings that have successfully 
interrupted transmission in the setting of presumptive treatment. If our hypothesis is correct and 
estimates of incidence in the RfMDA arm are accurate, approximately 78 index cases will be identified 
and 1,961 people will be treated in the RfMDA Target Areas.8,36 If the actual coverage is 80%, we 
would have a 95% confidence interval between 78% and 82% with this sample size. For the RACD 

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and RAVC interventions, we will be powered to measure 80% coverage, as the number of people that 
receive RACD or RAVC will be higher than received for RfMDA. 
 
11.5 
Secondary outcome on feasibility – Adherence to AL administered in RACD and 
RfMDA 
Adherence to medication will be measured by a pill count during follow up visits in all participants 
receiving medication in the RACD arm and in a selection of participants in the RfMDA arm see Table 
7. We expect that 26 EAs in the RfMDA arm will have at least one index case, and at least 25 people 
will be assessed per Target Area (26*25=650), for a total sample of 774 people (see Table 7). If the 
actual adherence were 80%, we would have a 95% confidence interval between 77% and 83% with 
this sample size. 
Table 7. Sample sizes for primary and secondary outcomes 
Outcome 
Result* 
 
Effective Sample Size (# of subjects 
unless otherwise indicated) 
Primary aim 
 
 
Cumulative Incidence 
18.81/1000 (RACD) vs. 7.84/1000 
(RfMDA) and 7.84/1000 (RAVC) vs. 
18.81/1000 (no RAVC) 
15,456 
Secondary aims  
 
 
Effectiveness 
 
 
Exposure (seroprevalence) 
10% (RACD) vs. 5.3% (RfMDA) and 
10% (no RAVC) vs. 5.3% (RAVC) 
4,860 
(does not include index cases) 
Infection prevalence 
n/a 
4,860 
(includes index cases) 
Feasibility 
 
 
Coverage 
80% (95% CI: 77%-83%) 
5,279 
Adherence 
80% (95% CI: 77%-83%) 
774 
Prevalence of SAEs  
n/a 
5,279 
Acceptability 
n/a 
5,279 
Cost 
n/a 
10 Target Areas/arm 
*For most secondary outcomes, power calculations were not performed; however, effective sample size is shown 
 
11.6 
HS RDT evaluation – To measure infection prevalence and the diagnostic accuracy 
of HS RDT 
For the purpose of the HS RDT evaluation, with a sample size of 5,040 we will have more than 80% 
power to detect a 4% point prevalence of malaria infection by HS RDT, with a precision of 10%. To 
measure the diagnostic accuracy of HS RDT using HRP II concentration or qPCR as a gold standard, 
we will have more than 90% power to measure a sensitivity of 65 to 99% with a precision of 10%, and 
a specificity of 91-99% with a precision of 1%. 
11.7 
Analysis 
Primary Analysis and Missing Data 
One-way frequency tables for all categorical variables and distributions, ranges, and outliers for 
continuous variables will be generated to perform range checks, quantify the amount of missing data, 
and generate descriptive findings that will characterize EA and Target Area characteristics in the study 
population. These analyses will be stratified by intervention group (i.e., RfMDA vs RACD and RAVC 
vs no RAVC) and we will describe the equality of group covariates at baseline. Although we expect 
the randomisation to produce balanced covariate structures, we will consider methods of adjustment 
to balance baseline covariates should there be differences between the arms.   
Interim Analysis 
After the first transmission season of the trial an interim analysis will be performed to determine 
progress and whether sample size will likely be met in the second year of the trial. 
Primary Analysis (incidence) 
Due to the lifecycle of P. falciparum in the mosquito and the distribution of distinct transmission 

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chains across space and time, an EA level impact of the intervention on transmission would not be 
expected for at least several weeks after the first intervention for an EA. Thus, cumulative incidence 
will be calculated after taking into account an 8-week lead-in period. 
For the primary analyses of the four study arms, there will be three major comparisons of incidence: 
between the RfMDA and RACD arms (28 EAs will receive RfMDA and 28 RACD), between RAVC 
and non RAVC arms (28 EAs each) and between the arm receiving RfMDA and RAVC (14 EAs) and 
the arm receiving RACD with no RAVC (14 EAs). For the primary comparisons, we will follow an 
intention-to-treat (ITT) approach. The null hypothesis is that there are no differences in incidence 
between study arms (all rate ratios = 1). We hypothesize that incidence will be reduced by 50% by 
RfMDA and 50% by RAVC, with a combined multiplicative reduction in the arm receiving both 
interventions (RR 0.25). For the primary ITT analyses, estimates of effect of each intervention will be 
estimated adjusting for the presence of the other intervention (i.e. the RfMDA vs. RACD analysis 
would be adjusted for the presence of RAVC), but without adjusting for any other co-variates. 
Outcomes will be assessed at the individual level.  
Proportional hazards regression for an individual’s survival to the first episode of malaria will also be 
performed based on a delayed window of eight weeks. Individual incident cases registered in the rapid 
reporting system will be tallied by EA. Using summary population data from the GR for each EA, the 
number of individuals in each EA who did not have an incident case of malaria reported will be 
calculated and a record generated for each hypothesized non-infected individual. These will be 
combined with the records for incident cases to create a dataset with one record for each individual in 
every EA. This dataset will be used to run a Cox hazard model of time to either incident infection or 
the date of dataset aggregation. The start time for each EA will be the date of the first intervention of 
the study period. Hazard models will adjust for clustering of observations by EA. Significance will be 
calculated using a robust “sandwich” estimator. To consider different criteria for intervention 
effectiveness, three models will be run: all cases postdating the first intervention of the study period; 
all cases excluding those with travel history (i.e., presumed imported cases); and all cases censoring 
those with either a travel history or a detection date within eight weeks of the first intervention of the 
study period. 
Because of the clustered nature of the data, our modelling approach will adjust for correlation of 
observations by EA for analyses using the overall sample and by both EA and Target Area for analyses 
using the Target Area sample. Generalized estimating equations (GEE) will be used to perform the 
proposed primary analyses. GEE accounts for the correlation of persons within clusters and EAs. GEE 
estimates are consistent even if the correlation structure is incorrectly specified, though GEE's 
statistical efficiency improves as the working correlation structure more closely approximates the 
actual correlation structure. Thus, several working correlation structures suitable for the study's design 
will be considered (e.g., unstructured, Autoregressive order 1, exchangeable). The Quasi-Akaike 
Information (QIC) statistic will be used to select the final working correlation structure. Robust Huber-
White "sandwich" standard errors will be used to obtain correct inferences even if the chosen 
correlation structure remains slightly mis-specified. Alpha will be set at 0.05 for all planned 
comparisons. 
Additional analyses will consider adjustments for variability in intervention timing and coverage, 
differential administration of single low dose primaquine in RACD versus RfMDA arms, proximity to 
the nearest household receiving an alternate intervention, and variation in EA characteristics that 
differed by intervention arm, including receipt of RAVC and/or RfMDA during the pilot phase of the 
study. 
Subgroup analyses 
Although power is limited by the constraints of the total number EAs in the study area, we will describe 
summary measures of incidence and intervention effects for some specific subgroups of interest within 

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our study area population, such as members of each gender and age group, migrants, children, and 
those living in particular areas.  
 
Secondary analyses  
If the preliminary analyses reveal an imbalance in the baseline covariates between the RfMDA vs 
RACD arms, and RAVC vs non-RAVC arms, a second set of models will be run for all primary 
analyses. Adjusted models will reweight the data (through inverse probability weighting, or targeted 
minimum loss based estimation) to recover effect estimates that reflect an equal distribution of baseline 
covariates.  
Assessments of secondary outcomes will be conducted using GEE techniques to account for the 
clustered nature of the data collection, as described above. For analyses of outcomes in the Target Area 
sample, clustering by both EA and Target Area will be accounted for in the modelling approach. 
Planned secondary analyses and hypotheses are as follows 
 
Hypotheses regarding the effectiveness of the different interventions: 
1. Comparison of seroprevalence using antibodies to markers of recent exposure. Upon analysis of 
samples collected in mid-2017, we expect to find lower seroprevalence in areas receiving RfMDA 
than in those receiving RACD, as well as those receiving RAVC vs no RAVC. 
 
Comparison of prevalence of malaria infection. We expect prevalence to be lower in Target 
Areas receiving RfMDA than in those receiving RACD, as well as those receiving RAVC vs no 
RAVC. 
 
Comparison of malaria incidence in the subsequent malaria season. A sustained or delayed 
impact of the study interventions on the reservoir of parasites in the community (in humans 
and/or the mosquito) may be evident subsequent season.  
 
 
Planned analyses of operational feasibility and expected findings: 
1. Coverage of the intervention. Coverage of the different interventions will be assessed using several 
different approaches depending on intervention arm. The numbers and proportion of the following 
intervention coverage indicators will be calculated by arm:  
a) Eligible cases investigated out of the eligible cases reported in the rapid reporting 
system;  
b) The participants completing finger prick testing (RACD arm), or receiving at least the 
first dose of medication (RfMDA arm) up to 25 per intervention out of the number of eligible 
residents living within 500 meters of the index case household up to 25 per intervention;  
c) Participants receiving AL per intervention (up to 25 per intervention) out of the number 
of eligible residents within 500 meters of the index case household (up to 25 per intervention);  
d) Households receiving spraying (RAVC arm) up to seven out of the index case and six 
closest households or all within 500 meters of the index case household; and  
e) Index case household members completing finger prick testing (RACD arm) or 
receiving at least the first dose of medication (RfMDA arm) up to 25 per intervention out of 
the number of eligible residents of the index household.  
 
The proportion of the people living in Target Areas around an index case that receive each intervention 
is expected to be 80% with a 95% confidence interval from 77% to 83%. 
 
2. Adherence to medication. In the subsample of Target Areas in the RfMDA arm and in all 
participants receiving medication in the RACD arm, we will assess the adherence to the three-day 
regimen of AL using a pill count. We expect adherence to be 80%. 
 

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3. Safety of the treatment/additional IRS. The number and percent of people experiencing an adverse 
event will be recorded by study arm. We expect that medications and insecticide will be safely 
administered with few or no serious adverse events related to the intervention. 
 
4. Acceptability of the intervention. Interviews and focused group discussions will be audio-recorded 
then transcribed and translated with a brief summary written for each interview. Transcripts will 
be coded and to identify major themes associated with the acceptance. We will describe facilitators 
and barriers to these strategies with the goal of identifying the most acceptable way to engage the 
community in malaria elimination. 
 
5. Costs per intervention event and per population. Detailed costing will be performed in 10 Target 
Areas per arm. We expect that costs per intervention event and per population for implementing 
RfMDA will be no higher than for RACD. 
 
Additional analyses 
The above described analytical approaches do not assess whether interventions protect individuals 
residing within intervention cluster but outside the range of focal intervention delivery. As such, we 
also propose to estimate spillover effects – the effects among individuals in intervention clusters but 
outside areas the directly received the intervention. First, we will estimate spillover effects of focal 
malaria elimination interventions on malaria incidence and prevalence. There is a strong biological 
basis for spillover effects of malaria interventions that deliver transmission-blocking drugs (22–24) as 
well as indoor residual spraying, which reduces the number of local vectors. Thus, we hypothesize that 
reactive interventions for malaria elimination produce spillover effects among untreated individuals in 
areas where treatment was delivered. Second, we will assess whether spillover effects of focal malaria 
elimination vary by distance to treatment and implementation factors such as coverage and timing 
relative to incident cases. We hypothesize that spillover effects will increase with intervention 
coverage and decrease with distance to treatment.  
While first question will measure the magnitude of spillover effects, the second will provide 
information about the spatial distribution of spillover effects and the extent to which treatment 
coverage modifies spillover effects. We will utilize novel semi-parametric methods appropriate for 
infectious disease data that impose minimal modeling assumptions, minimizing bias. Findings will 
supplement the main analyses to inform whether these interventions can succeed in eliminating malaria 
at scale or whether they require tailoring to better reach hot spots of transmission.  
 
Additionally, we propose to use results from the described analytical approaches to parameterize a 
mathematical model of malaria transmission designed to assess the relative benefits of RfMDA vs. 
RACD and insecticide-based strategies such as reactive spraying (RS). A small number of modeling 
studies have been carried out to assess the efficacy of RACD for malaria elimination (e.g. Gerardin et 
al., 2017, https://malariajournal.biomedcentral.com/articles/10.1186/s12936-017-1903-z); however, 
no modeling studies have been conducted that align with field studies and address realistic intervention 
and logistical costs in elimination settings of interest. We will utilize an individual-based model of 
malaria transmission, taking into account both the human host and mosquito vector population 
dynamics. Using the above analytical approaches to parameterize this model, we will explore the cost-
effectiveness of RfMDA, RACD and RS, and determine optimal intervention parameters, such as the 
optimal radius of screening and treatment in response to a detected case, etc. 
 
Finally, leveraging the spatial data available in this study, we will perform secondary analyses 
whereby survey case data will be used in combination with open-access data sources to predict 
housing types and mosquito habitats, and incorporate this spatial information into malaria risk 
mapping models. The goal of the analysis is to identify areas suitable for building improvement 
projects and targeted vector control. 

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12.0 Ethics considerations 
12.1 
Consent  
The following consents will be conducted: 
Table 8. Informed consent overview 
Subject/Activity 
Informed consent covers 
Index case, Case investigation 
 
Informed consent for DBS collection 
None needed for RDT or case investigation form as they are usual MoHSS 
protocol. 
RACD  
At enrolment:  
<0000> 
Brief questionnaire and GPS mapping. 
<0000> 
RDT test, treatment if positive, referral to health facility if 
indicated 
<0000> 
Storage of blood with DBS. 
Post intervention:  Potential focus group discussion  
RfMD
A  
At enrolment: 
<0000> 
Brief questionnaire and GPS mapping. 
<0000> 
3 day course of antimalarial treatment by modified DOT. 
<0000> 
Additional IRS if in RAVC arm 
<0000> 
Post intervention: 
<0000> 
Potential pill count. 
<0000> 
Potential focus group discussion 
Resident Enrolment, 
Intervention  
All residents of Target Areas 
RAVC 
At enrolment: 
<0000> 
Brief questionnaire and GPS mapping 
<0000> 
Assistance moving household items 
<0000> 
Spraying of walls and ceiling of all sleeping structures 
Serology Follow-ups  
Index cases from Phase I case-control 
study; Secondary cases and some 
RDT-negative controls from RACD 
EAs. 
● At 6-12 and 12-24 months after diagnosis (Note: The study team will 
seek consent at both of these visits) 
● Follow-up blood testing with RDT, treatment if positive, & referral to 
health facility if indicated (see Protocol)  
● Storage of blood with microtainer and DBS. 
Resident Enrolment, Endline 
survey 
All residents of study Enumeration 
Areas 
At endline survey study:  
<0000> 
Brief questionnaire and GPS mapping 
<0000> 
Follow-up blood testing with RDT, treatment if positive, & referral 
to health facility if indicated  
<0000> 
Blood testing with new highly sensitive RDT 
<0000> 
Storage of blood with DBS and microtainer. 
Acceptability Assessment 
 Participants selected for inclusion in 
Acceptability Assessment 
Participation in qualitative interview and/or focus group after intervention 
 
Written informed consent will be obtained from the household members and neighbours eligible for 
the study. For the qualitative assessment, verbal informed consent will be obtained for study 
participants. For the field procedures (survey, blood testing, and follow-up visits), people will be asked 
to consent each time they are eligible to be part of the study. Consent will not be required for collection 
of de-identified, used RDTs from health facilities inside and outside of the Zambezi region, if this 
collection is deemed feasible.  
Consent will be conducted in the participant’s house prior to study activities. Consents may be 
collected from all members of the household at once. Parents will be able to sign one form to consent 
for themselves and all of their participating children (under18 years old) at once. Each additional adult 

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member of the house will sign separate consent forms. Each minor (12-17 years old) will sign a 
separate assent form.  
Informed consent will be conducted in SiLozi, the most universal local dialect, or English, per 
participant preference, and an interpreter will be used if necessary. Consent forms will be available in 
English and SiLozi, and if the consent is conducted in neither of these, the language of consent will be 
documented and a witness who speaks the same language will be asked to sign to confirm the informed 
consent process. If the participant is unable to read or write, an X will substitute for a signature. All 
signatures will be collected on the tablet and stored electronically, linked to the related questionnaire. 
As part of the informed consent process, study personnel will assess participants’ understanding of the 
study procedures that were explained by using a checklist comprised of key components of the study. 
Participants who pass will be allowed to sign the written consent form. If the participant does not pass, 
the consent discussion will be repeated, before asking for a signature. In this case, the consent form 
will be read again, focusing on areas where understanding was limited, and encouraging the subject to 
ask questions. Up to five attempts will be permitted per participant. If, despite five consecutive attempts 
(each incorrect one followed by the team’s correction with explanation), the participant still has not 
answer a minimum number of questions correctly, then he/she will not be allowed to take part in 
RfMDA.  
12.2 
Management of sick participants 
During the intervention, individuals with complicated malaria or symptoms requiring further 
evaluation will be referred for evaluation at the nearest health facility. 
12.3 
IRBs 
The study protocol, as well as all informed consent documents and future revisions will be reviewed 
and approved by corresponding IRBs before the study launch. The University of California, San 
Francisco CHR will provide the primary review. The London School of Hygiene and Tropical 
Medicine will also provide a full review, with the knowledge that UCSF is also reviewing. The MoHSS 
and UNAM will conduct protocol reviews. No outside IRB will rely on the UCSF CHR review.  
 
Site Information: 
University of Namibia 
340 Mandume Ndemufayo Ave 
Pioneers Park, Windhoek, Namibia 
 
Ministry of Health and Social Services 
Ministerial Building, Harvey St 
Private Bag 13198 
Windhoek, Namibia 
 
London School of Hygiene and Tropical Medicine 
Keppel St 
London, UK WC1E 7HT 
 
12.4 
Governance 
Namibia Malaria Elimination Research Partnership Steering Committee (NAMEP) 
Role of the Steering Committee 
The role of Steering Committee will be to support the implementation of research, interpretation of 
findings, and broader dissemination of findings to produce national and international impact. By 
making recommendations, the Steering Committee will provide oversight to ensure that the research 
is well coordinated, scientifically and ethically sound, and in line with the MoHSS’ goals for malaria 

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elimination in Namibia. Not all committee members are expected to be directly involved in the project 
outside of protocol review and annual meetings. (See Appendix R for Terms of Reference} 
Membership of Steering Committee 
The Steering Committee for NAMEP will provide guidance and oversight for this research. The 
NAMEP Steering Committee was established in April 2014 to support Namibia in its goal to eliminate 
malaria. Members of the Steering Committee are senior representatives of the institutions collaborating 
to implement the NAMEP program, which involves working to develop and test innovative 
surveillance and response strategies in Zambezi region. The NAMEP Steering Committee includes 
people from the University of California, San Francisco, the Ministry of Health and Social Services, 
National Vector-borne Diseases Control Program, The University of Namibia, Multidisciplinary 
Research Centre, The London School of Hygiene and Tropical Medicine, the Clinton Health Access 
Initiative, Witswatersrand University, and the Novartis Foundation. 
Activities of the Steering Committee 
The Steering Committee will meet once yearly in Namibia to review and provide recommendations to 
this project. In addition, they will participate in teleconferences one to two times a year to provide 
additional input on project preparation, implementation, and progress. International members will be 
encouraged to join the annual Steering Committee meeting in person, however may join by 
teleconference if schedules limit travel to Namibia. Steering Committee members will also have 
ongoing interactions with study team members on an as needed basis. 
12.5 
Potential Limitations 
Malaria declines: There is a possibility that the number of cases detected in Zambezi could drop 
significantly and impact our ability to collect sufficient data to draw conclusions about malaria 
epidemiology in Zambezi region. However, given the current assumptions and malaria incidence, 
which was 19.5 cases/1,000 residents from 2013 to 2014, this is unlikely to be a problem. However, if 
this occurs, and we would no longer be powered to assess the primary aim, the study could expand to 
additional health facilities within Zambezi region or extend another year. These issues will be 
addressed in the interim analysis. 
Malaria increases: Due to climate, intrinsic disease dynamics, or regional increases, or changes in 
MoHSS implementation of standard malaria prevention strategies, the malaria burden in Zambezi 
region could increase over the study period. This occurred during the 2016 season, significantly 
affecting the study. The malaria burden in regions of Namibia near Zambezi region, as well as malaria 
in areas of Angola, Zambia, and Botswana that border the region will influence local malaria incidence. 
Increases in malaria burden in Zambezi region and surrounding areas will mean that health facility 
staff will experience a higher case load than they are currently, perhaps leaving them less time to 
complete case investigation forms and participate in any other study activities. The program will 
monitor ongoing malaria incidence and completion of tasks necessary for the project and will adjust 
staffing accordingly. Additionally, it may be necessary to increase the threshold for an intervention 
response (e.g. > 1 incident case). If this change is made, the same change will be made to all study 
arms and therefore should not affect the comparability of the arms as long as there are enough teams 
to maintain sufficient coverage. 
Implementation of a drug change partway through the study: The drug regimen for both RfMDA 
and RACD will be based on the national first line treatment for uncomplicated Pf malaria. At present, 
the first line treatment is AL. A new policy was approved that includes the use of single dose PQ with 
AL for its anti-gametocidal properties. As our study is nested within operations of the NVDCP, we 
may change the drug regimen for RACD to AL+PQ partway through the study. However, we do not 
anticipate that this will affect our ability to distinguish impact between the study arms of the trial. As 
the study should have similar numbers of index cases in all arms of the study, the transmission blocking 
impact on index cases will be balanced. In the event that the use of PQ has a greater than expected 
impact on transmission in the RACD arm, we may need to increase the sample size of the study by 
lengthening the study period. 

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Data quality and management: Data collection will occur in various locations by different team 
members and there is potential for inconsistencies. However, all team members will receive 
comprehensive training and supervision to ensure data quality. To ensure data quality the Data 
Manager will sample a proportion of case investigation forms to ensure that they are complete and that 
data are entered correctly into the database and the SDSS. Additionally, occasional sampling of case 
registers will occur to ensure that all malaria cases are being reported to the Surveillance Officer.  
Barcode labels will be used to link blood samples to data collection forms. The Site Manager and 
Surveillance Officer will provide oversight to maintain study procedures. All team members will 
receive regular updates on interim study findings to promote ownership of the study and maintain 
interest. 
Laboratory capacity LAMP, PCR, ELISA, and genotyping are relatively straightforward procedures 
and we do not expect the laboratory technologists to have any difficulty, as they already have 
experience with these methods. However, if it is not possible to perform these procedures reliably in 
either Zambezi region at the MoHSS reference laboratory or in Windhoek at the UNAM laboratory, 
we will transfer samples to the UCSF laboratory for testing.  

50 
13.0 Timeline
Year or Quarter 
Milestones 
Expected outcomes and 
related activities 
Year 2  
1/-12/2015 
Year 3  
1/-12/2016 
Year 4  
1/17-12/17 
Afte
r 
Year 
4 
 
Study preparation 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
● Develop, review, and finalize work plan & protocol. In-country review; incorporate feedback into protocol. 
Finalize protocol. 
● Randomize EAs. Sensitization of participating EAs. 
● Complete & submit applications to IRBs.  
● Finalize & translate informed consents. 
● Finalize questionnaires. 
Trainings 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
● Finalize & translate training materials. 
● Conduct trainings for lab and field personnel. 
Study intervention 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
● Finalize SOPs for field procedures. 
● Order supplies (drugs, insecticide, field supplies). 
● Field team conducts case investigations & deploys RACD or RfMDA +/-RAVC. 
Adverse event 
monitoring 
 
 
 
 
 
 
 
 
 
 
 
 
● When adverse events occur, collect additional data to assess causality. 
● Prepare reports of serious adverse events. 
Data collection:  
Laboratory assessment 
 
 
 
 
 
 
 
 
 
 
 
 
● Finalize SOPs for lab procedures. 
● Order supplies. 
● Ongoing blood surveys for LAMP/PCR in RACD arm. 
Data collection: outcome 
measures 
 
 
 
 
 
 
 
 
 
 
 
 
● Perform routine surveillance for incidence data.  
● Collect & coordinate the endline survey, expected mid 2017 (blood samples for infection prevalence and 
serology). 
● Collect operational feasibility outcome measures – coverage, safety (adverse event monitoring above), costs, 
and adherence. 
Data collection for 
Acceptability study, 
qualitative assessment 
 
 
 
 
 
 
 
 
 
 
 
 
● Finalize SOPs for qualitative assessment of acceptability. 
● Field team performs FGDs and in-depth interviews with study participants and key stakeholders. 
Project Monitoring 
 
 
 
 
 
 
 
 
 
 
 
 
● Develop and finalize SOP for monitoring project data. 
● Database check-ins. 
● Coordinate and hold annual and ad-hoc meetings of the DSMB and the Advisory Committee. 
Preliminary data 
analysis 
 
 
 
 
 
 
 
 
 
 
 
 
● Develop and finalize SOPs for data analysis. 
● Preliminary analysis on coverage, acceptability, cost-effectiveness, safety, and incidence, 
Final data analysis 
 
 
 
 
 
 
 
 
 
 
 
 
● Final analysis of coverage, prevalence of SAEs, acceptance, cost-effectiveness, incidence, parasite prevalence, 
seroprevalence, etc. 
Prepare final 
manuscripts and reports 
 
 
 
 
 
 
 
 
 
 
 
 
● Prepare manuscripts for publication. 
● Review with collaborators, incorporate feedback into manuscripts. 

51 
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15.0 Appendices 
A. Summary of Phase I surveillance and capacity building activities 
B. Study information for stakeholders 
C. Index Case Investigation Form 
D. Community Level Investigation Tracking Form 
E. Household Level Questionnaire 
F. Individual Level Questionnaire 
G. Modified DOT Record 
H. Pill Count and Adverse Events 
I. AL weight-based dosing 
J. Modified DOT Dosing Schedule 
K. Qualitative Key Informant Interview Guide 
L. Qualitative Focus Group Discussion Guide 
M. Adverse Events SOP 
N. MoHSS Serious Adverse Event Report Form 
O. WHO Toxicity Grading Scale 
P. Data and Safety Monitoring Board Terms of Reference 
Q. Consent Forms 
R. Steering Committee Terms of Reference 
S. Serology Sub-study Questionnaire 
T. XS Survey Household listing and clinical forms 
U. XS Survey Household questionnaire 
V. XS Survey Individual questionnaire 
W. rfMDA quiz