HIV-1 & Coronavirus-Coinfection in Europe: Morbidity & Risk Factors of COVID-19 in People Living With HIV
Conditions: HIV-1-infection, COVID-19
Sponsor: NEAT ID Foundation

NEAT ID HIV CoCo PROTOCOL V 3.0 dated 29 Aug 2022  
 
 
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HIV-1 & Coronavirus-Coinfection in Europe: Morbidity & Risk Factors of COVID-19 in People Living 
With HIV 
 
 
NCT: NCT05481216 
 
 
Date: 29 August 2022  
 

NEAT ID HIV CoCo PROTOCOL V 3.0 dated 29 Aug 2022  
 
 
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HIV-1 & Coronavirus-Coinfection in Europe: Morbidity & Risk 
Factors of COVID-19 in People Living With HIV 
- HIV CoCo - 
 
Version 3.0 dated 29 August 2022  
Sponsor Protocol ID: 303CoCo  
 
 
 
SPONSOR: NEAT ID - The European treatment network of  
HIV, hepatitis and global infectious diseases 
 
PLEASE DISCARD PREVIOUS COPIES AND RETAIN ONE FOR THE SITE FILE 
 
 
 
 
 
 
 
Private & Confidential 
 
 
 
 
 
Compliance Statement: 
This study will be conducted in accordance with the International Society for Pharmacoepidemiology (ISPE) 
guidelines of Good Pharmacoepidemiology Practice (GPP), the GDPR and other applicable data privacy 
legislation and Heads of Medicines Agencies (HMA) including archiving of essential documents and all 
applicable regulatory requirements. 
 
Confidentiality Statement: 
The information contained in this document, particularly unpublished data, is the property or under control of 
NEAT ID, and is provided to you in confidence as an investigator, potential investigator, or consultant, for 
review by you, your staff, and an applicable Institutional Review Board or Independent Ethics Committee. 
The information is only to be used by you. You will not disclose any of the information to others without 
written authorization from NEAT ID 

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SPONSOR AND CHIEF INVESTIGATOR SIGNATURE PAGE 
 
The undersigned confirm that the following protocol has been agreed and accepted and that the Chief 
Investigator agrees to conduct the study in compliance with the approved protocol and will adhere to 
the principles outlined in the ISPE guidelines of Good Pharmacoepidemiology Practice (GPP) and 
Heads of Medicines Agencies (HMA), the GDPR and other applicable Data Protection legislation, GCP 
guidelines, the Sponsor’s SOPs, and other regulatory requirements as applicable or as amended. 
 
I agree to ensure that the confidential information contained in this document will not be used for any 
other purpose other than the evaluation or conduct of the clinical investigation without the prior 
written consent of the Sponsor. 
 
I also confirm that I will make the findings of the study publicly available through publication or other 
dissemination tools without any unnecessary delay and that an honest accurate and transparent 
account of the study will be given; and that any discrepancies from the study as planned in this 
protocol will be explained. 
 
For and on behalf of the study Sponsor: 
 
 
Signature: 
................................................................................................ 
 
 
 
Date: ........../……....../………..... 
 
 
Name: (please print): 
...................................................................................................................................................... 
 
 
 
Chief Investigator: 
 
 
Signature: 
................................................................................................ 
 
 
 
Date: ........../……....../………..... 
 
 
Name: (please print): 
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STATISTICIAN OR STUDY ANALYST SIGNATURE PAGE 
 
The undersigned confirm that the following protocol has been agreed and accepted and that the 
Statistician or Study Analyst agrees to conduct the study in compliance with the approved protocol, 
Statistical Principles for Clinical Trials, ICH E10 and will adhere to the principles outlined in the ISPE 
guidelines of Good Pharmacoepidemiology Practice (GPP) and Heads of Medicines Agencies (HMA), 
the GDPR and other applicable Data Protection legislation, GCP guidelines, the Sponsor’s SOPs and 
other regulatory requirements as applicable or as amended. 
 
I agree to ensure that the confidential information contained in this document will not be used for 
any other purpose other than the evaluation or conduct of the clinical investigation without the 
prior written consent of the Sponsor. 
 
I also confirm that I will make the findings of the study publicly available through publication or 
other dissemination tools without any unnecessary delay and that an honest accurate and 
transparent account of the study will be given; and that any discrepancies from the study as planned 
in this protocol will be explained. 
 
 
Statistician or Study Analyst: 
 
 
Signature: 
................................................................................................ 
 
 
 
Date: ........../……....../………..... 
 
 
Name: (please print): 
...................................................................................................................................................... 
 
 
 
 

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PRINCIPAL INVESTIGATOR SIGNATURE PAGE 
 
I agree to conduct the study in accordance with principles outlined in the ISPE guidelines of Good 
Pharmacoepidemiology Practice (GPP) and Heads of Medicines Agencies (HMA), the GDPR and other 
applicable Data Protection legislation,  ICH-GCP the applicable regulatory requirements and with the 
approved protocol. 
 
I agree to comply with the procedures for data recording/reporting 
 
I agree to permit monitoring, auditing and inspection at this site and to retain all study related 
essential documentation for the duration of the study as necessary. 
 
Principal Investigator: 
 
 
Signature: 
................................................................................................ 
 
 
 
Date: ............./……........./………..... 
 
 
Name: (please print): 
............................................................................................................................................................ 
 
 
 
 

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TABLE OF CONTENTS 
 
 
SPONSOR AND CHIEF INVESTIGATOR SIGNATURE PAGE............................................................................. 3 
STATISTICIAN OR STUDY ANALYST SIGNATURE PAGE ................................................................................ 4 
PRINCIPAL INVESTIGATOR SIGNATURE PAGE ............................................................................................ 5 
TABLE OF CONTENTS ............................................................................................................................... 6 
KEY STUDY CONTACTS ............................................................................................................................. 8 
STUDY SYNOPSIS ..................................................................................................................................... 9 
FUNDING AND SUPPORT ....................................................................................................................... 11 
LIST OF ABBREVIATIONS ........................................................................................................................ 12 
1. 
BACKGROUND .............................................................................................................................. 13 
2. 
RATIONALE ................................................................................................................................... 13 
3. 
OBJECTIVES AND OUTCOME MEASURES/ENDPOINTS ...................................................................... 14 
3.1 
PRIMARY OBJECTIVE ................................................................................................................... 14 
3.2 
SECONDARY OBJECTIVES .............................................................................................................. 14 
3.3 
PRIMARY ENDPOINT/OUTCOME ..................................................................................................... 14 
3.4 
SECONDARY ENDPOINTS/OUTCOMES ............................................................................................... 15 
4 
STUDY DESIGN .............................................................................................................................. 15 
4.1 
STUDY SCHEMA ......................................................................................................................... 15 
5 
ELIGIBILITY CRITERIA ..................................................................................................................... 16 
5.1 
INCLUSION CRITERIA ................................................................................................................... 16 
5.2 
EXCLUSION CRITERIA .................................................................................................................. 17 
6 
STUDY PROCEDURES ..................................................................................................................... 17 
6.1 
SUBJECT IDENTIFICATION.............................................................................................................. 17 
6.2 
DATA COLLECTION ...................................................................................................................... 17 
7 
STATISTICS AND DATA ANALYSIS .................................................................................................... 18 
7.1 
SAMPLE SIZE CALCULATION ........................................................................................................... 18 
7.2 
PLANNED RECRUITMENT RATE........................................................................................................ 19 
7.3 
STATISTICAL ANALYSIS PLAN .......................................................................................................... 19 
7.3.1 
Summary of baseline data and flow of patients ..................................................................... 19 
7.3.2 
Primary outcome analysis ................................................................................................... 20 
7.3.3 
Secondary outcome analysis ............................................................................................... 20 
7.4 
SUBJECT POPULATION ................................................................................................................. 20 
7.5 
PROCEDURE(S) TO ACCOUNT FOR MISSING OR SPURIOUS DATA ................................................................ 21 
8 
DATA HANDLING ........................................................................................................................... 21 

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8.1 
DISSEMINATION OF RESULTS, AUTHORSHIP ELIGIBILITY GUIDELINES AND ANY INTENDED USE OF PROFESSIONAL WRITERS
 
21 
8.2 
DATA PROTECTION ..................................................................................................................... 21 
8.3 
DATA RETENTION ...................................................................................................................... 22 
9 
ETHICAL AND REGULATORY CONSIDERATIONS ................................................................................ 22 
9.1 
RESEARCH ETHICS COMMITTEE (REC) REVIEW & REPORTS ..................................................................... 22 
9.2 
PEER REVIEW ............................................................................................................................ 22 
10 
REFERENCES ................................................................................................................................. 23 
11 
APPENDICIES ................................................................................................................................ 26 
APPENDIX 1 – COMORBIDITY VARIABLES & DEFINITIONS ......................................................................... 26 
APPENDIX 2 – AMENDMENT HISTORY .................................................................................................... 28 
 
 

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KEY STUDY CONTACTS 
 
Chief Investigator 
Prof. Georg Behrens 
Department for Rheumatology and Immunology, OE 6830 
Hannover Medical School 
Carl-Neuberg-Str. 1 
30625 Hannover 
Germany 
Sponsor 
NEAT ID Foundation (NEAT ID) 
Registered address: PL 709 Rue Haute 322, 1000 Brussels, 
Belgium  
Administrative office: 27 Old Gloucester Street, London WC1N 
3AX, UK 
Project Management 
HIV CoCo Project Manager 
Research Organisation (KC) Ltd. (ROKC)  
The Stanley Building, 7 Pancras Square, London, UK, N1C 4AG 
HIVCoCo@ROKCservices.com  
Data Management 
Clinical Informatics Team  
Research Organisation (KC) Ltd. (ROKC)  
The Stanley Building, 7 Pancras Square, London, UK, N1C 4AG 
Statistics 
Lambert Assoumou 
Inserm and Sorbonne University 
56, Boulevard Vincent Auriol,  
CS 81393 - 75646 Paris cedex 13, France 
lambert.assoumou@iplesp.upmc.fr  
 
 
 
 

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STUDY SYNOPSIS 
 
Full study Title 
HIV-1 & Coronavirus-Coinfection in Europe: Morbidity & Risk Factors of 
COVID-19 in People Living With HIV (PLWHIV) 
Short title/Acronym 
HIV CoCo 
Clinical Phase  
Observational Study 
Study Design 
Retrospective, case-control study 
Study Population & 
Planned Sample Size 
Cases: 500 PLWHIV with COVID-19 
Controls: 1,000 PLWHIV without COVID-19 & upto 1500  HIV seronegative 
COVID-19 patients 
Eligibility Criteria 
Cases: at least 18 years of age with documented HIV-1 infection and confirmed 
SARS-CoV-2 infection by documented, or patient-reported, positive result on 
PCR testing of a nasopharyngeal or respiratory sample, before 1st April 2021. 
Controls: at least 18 years of age with either: documented HIV-1 infection; or 
confirmed SARS-CoV-2 infection by documented, or patient-reported, positive 
result on PCR testing of a nasopharyngeal or respiratory sample, before 1st April 
2021. Controls must also meet the matching criteria.  
Indication 
HIV & COVID-19 
Methodology 
Only real-world retrospective data will be used for this study. Deidentified 
retrospective data will be transcribed into the eCRF system from source data at 
each clinical site or from existing COVID-19 cohort databases, where 
appropriate. No personal identifiable data will be transmitted to NEAT ID.  
 
Each case will be matched to control as per the criteria set out below: 
 
For comparing PLWHIV & COVID-19 versus HIV seronegative COVID-19 patients, 
a 1:1 or 1:3 matching will be performed according to the following criteria:  
• 
Age (+/- 5 years) 
• 
Sex 
• 
Ethnicity (where available) 
• 
Month of COVID-19 diagnosis (+/- 2 months) 
• 
COVID-19 diagnosis inpatient, 1:1 matching 
OR 
• 
COVID-19 diagnosis outpatient (ambulatory), 1:3 matching 
 
For comparing PLWHIV & COVID-19 versus PLWHIV without COVID-19, a 1:2 
matching for similar risk of acquiring COVID-19 will be performed according to 
the following criteria:  
• 
Age (+/- 5 years) 
• 
Sex 
• 
Ethnicity (where available) 
Number of sites 
Up to 30 sites 

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Objectives 
Primary 
1.  To describe outcomes of 
COVID-19 in PLWHIV in 
comparison to HIV 
seronegative COVID-19 
controls. 
2.  To identify risk factors 
(e.g. CD4 cell nadir, 
current CD4 count, co-
morbidities) for severe 
COVID-19 outcomes 
within the group of 
PLWHIV. 
 
Secondary 
1. To describe differences in the clinical 
manifestation of COVID-19 in PLWHIV as 
compared to HIV seronegative controls. 
2. To describe the response to treatment, 
including supportive care and novel 
therapeutics against COVID-19, including 
antiviral or immunomodulatory therapy 
3. To describe the co-morbidities in PLWHIV 
and controls with COVID-19 
4. To compare the COVID-19 severity in 
PLWHIV and controls at diagnosis and 
hospital admission. 
 
Outcome Measures 
Primary 
1. The primary endpoint is 
a composite of: Critical 
care admission (high 
dependency unit or 
intensive care unit), 
mortality in hospital or 
palliative discharge when 
discharged from hospital, 
or mortality at 6 weeks 
after diagnosis of COVID-
19 or at discharge from 
hospital (where 
applicable) 
Secondary 
1. Hospitalisation for COVID-19 
2. Length of stay in hospital 
3. Length of stay on ICU 
4. Number of ventilator-free days (VFDs) 
5. Length of extracorporeal membrane 
oxygenation (ECMO) 
6. Need for kidney replacement therapy 
7. Measurement of total comorbidity burden 
using the Charlson Comorbidity Index (CCI) 
and age-adjusted CCI (ACCI) 
8. Estimate risk of 30-day mortality after 
COVID-19 infection using pre-COVID health 
status (estimated using the Veterans 
Health Administration COVID-19 (VACO) 
index) 
9. Inflammatory marker and blood cell counts 
at COVID-19 diagnosis 
 
 
 

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FUNDING AND SUPPORT  
 
FUNDER(S) 
Gilead Sciences, Inc. 
333 Lakeside Drive 
Foster City, CA 94404 
NEAT ID Foundation (NEAT ID) 
Registered address: PL 709 Rue Haute 322, 1000 Brussels, Belgium 
Administrative office: 27 Old Gloucester Street, London, WC1N 3AX, UK 
COLLABORATORS/KEY CONTRIBUTORS 
Research Organisation King’s Cross (KC) Ltd. 
The Stanley Building, 7 Pancras Square, London, UK, N1C 4AG 
Prof. Anton Pozniak 
NEAT ID Foundation (NEAT ID) 
Registered address: PL 709 Rue Haute 322, 1000 Brussels, Belgium 
Administrative office: 27 Old Gloucester Street, London WC1N 3AX, UK 
Lambert Assoumou 
Inserm and Sorbonne University 
56, Boulevard Vincent Auriol,  
CS 81393 - 75646 Paris cedex 13, France 
 
 
 

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LIST OF ABBREVIATIONS 
 
Acronym 
Description 
ACCI 
Age-adjusted Charlson Comorbidity Index 
ART 
Antiretroviral Therapy/Treatment 
ARV 
Antiretroviral 
CCI 
Charlson Comorbidity Index 
CI 
Chief Investigator 
CRF 
Case Report Form 
CRO 
Contract Research Organisation 
CTA 
Clinical Trial Authorisation 
EC 
European Commission 
ECMO 
Extracorporeal Membrane Oxygenation 
eCRF 
Electronic Case Report Form 
EMEA 
European Medicines Agency 
EU 
European Union 
EUCTD 
European Clinical Trials Directive 
GDPR 
General Data Protection Regulation 
GCP 
Good Clinical Practice 
GPP 
Good Pharmacoepidemiology Practice  
HIV 
Human Immunodeficiency Virus 
ICH 
International Conference on Harmonisation of technical 
requirements for registration of pharmaceuticals for human 
use. 
ISF 
Investigator Site File 
ISPE 
International Society for Pharmacoepidemiology 
MS 
Member State 
R&D 
Research & Development   
PI 
Principal Investigator 
PLWHIV 
People Living With HIV 
REC 
Research Ethics Committee 
SOP 
Standard Operating Procedure  
TMF 
Trial Master File 
VACO 
Veterans Health Administration COVID-19 
VFD(s) 
Ventilator-Free Day(s) 
 
 
 

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1. BACKGROUND 
 
COVID-19 is a public health emergency of international concern with mortality rates of 2-4% and 
highest death risk in elderly male patients and those with co-morbidities. Little is known about the 
disease course of COVID-19 in specific patient groups with immunosuppression or people living with 
HIV (PLWHIV) [1-5] and whether PLWHIV may have some degree of protection due to their ART 
compounds [6-9]. Irrespective of their antiretroviral therapy, PLWHIV with co-morbidities are 
expected to accumulate risk factors for COVID-19. Also, incomplete immune reconstitution may put 
them at risk for severe COVID-19.  
2. RATIONALE  
 
Current evidence indicates that the risk of severe COVID-19 illness increases with age, male gender 
and with certain chronic medical problems such as arterial hypertension, cardiovascular disease, 
chronic lung disease, obesity and diabetes. Whether or not PLWHIV on treatment with a normal CD4 
cell count and suppressed HIV-RNA are at an increased risk of serious illness or death, many will have 
other conditions that increase their risk. Indeed, almost half PLWH in Europe are older than 50 years 
and chronic medical conditions, including cardiovascular and chronic lung disease, are more common 
in PLWHIV.  
Case series of PLWHIV with COVID-19 from China, Spain, Germany, Italy and the United States [10-22] 
show no clear evidence for a higher COVID-19 infection rate or different disease course in people with 
and without HIV. Of note, most case series of PLWHIV report a younger age in their study population 
than in HIV-negative hospitalised COVID-19 patients, but comparable rates of comorbidities. A cohort 
study from the United Kingdom reported a small potential increase in the risk of mortality among 
PLWHIV once hospitalised with COVID-19, albeit with no data around the risk of developing severe 
COVID-19 or hospitalisation among this cohort in the first place and no data on antiretroviral therapy 
(ART), viral load (VL) or CD4 count [23].  
An analysis of risk factors for COVID-19 deaths in the Western Cape [24] described after adjusting for 
other risk factors that HIV increased a COVID-19 patient’s death risk by a factor of 2.14 (95% CI 
1.70;2.70), and active TB by a factor of 2.70 (95% CI 1.91-4.04). Finally, Spanish researchers described 
the incidence of COVID-19 and risk of hospitalization among 77,590 PLWHIV receiving ART [7]. During 
a 3-month period, 236 PLWHIV were diagnosed with COVID-19, and 151 were hospitalized. The risk of 
hospitalization by NRTI treatment per 10,000 persons was lowest for TDF/FTC (10.5), while other NRTI 
strategies were similar.  
Data regarding the activity of TDF against SARS CoV-2 is conflicting. In Silico data suggests that TDF/FTC 
may bind to SARS CoV-2 Nsp1 protein [25], an unreviewed study shows that TDF and TAF may inhibit 
the SARS-CoV-2 polymerase [26], one in vitro study supports antiviral activity of TDF/FTC [27] and an 
animal models suggest shortened duration of symptoms, and possibly infectiousness [28]. However, 
two studies have failed to demonstrate any in vitro activity of tenofovir against CoV-2 [29,30]. There 
is ongoing discussion and research around other antiretrovirals, which may have some activity against 
COVID-19. The first randomised clinical trial (RCT) with lopinavir-ritonavir (LPV/r) demonstrated no 
benefit over standard care in 199 hospitalised adults with severe COVID-19 [31]. Since then the large 
UK RECOVERY trial, which to date has randomised almost 12,000 people hospitalised with COVID-19 
to different therapeutic options, has stopped recruitment to the LPV/r arm after a review by Data 
Monitoring Committee revealed no benefit of LPV/r over standard of care in terms of mortality, 
ventilation requirement or length of stay [32]. Moreover, an Italian case series suggests boosted DRV 

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does not prevent SARS-CoV-2 infection in PLWHIV or protect against worsening respiratory function 
[33]. 
Rapid data collection and analysis about COVID-19 in PLWHIV will depend on international multi-
centre collaborations, for which NEAT ID has a strong expertise. The majority of PLWHIV in Europe are 
in routine clinical care, allowing for a comprehensive data collection about COVID-19 and studying the 
impact of HIV drugs and specific risk factors. The NEAT ID COVID-19 Coinfection Dashboard was 
established in March 2020 to collect data on the number of PLWHIV co-infected with COVID-19 in 
Europe and has provided evidence that a significant number of PLWHIV are suffering from COVID-19 
in Europe already and that these individuals can be enrolled into an Epidemiology and Real-World-
Data study. 
There are two central questions to address:  
1. Is there a particular risk for COVID-19 in PLWHIV as compared to HIV seronegative control COVID-
19 cases? 
2. Are there particular factors, within the group of PLWHIV, which put them at risk for a more severe 
COVID-19 disease course? 
 
3. OBJECTIVES AND OUTCOME MEASURES/ENDPOINTS 
 
It is hypothesised that HIV infection is a risk factor for more severe COVID-19 outcomes and that 
advanced immunodeficiency as defined by current CD4 T-cell count or CD4 T-cell nadir is a risk factor 
for more severe COVID-19 outcomes in PLWHIV. 
 
3.1 Primary objective 
 
1. To describe outcomes of COVID-19 in PLWHIV in comparison to HIV seronegative COVID-19 
controls. 
2. To identify risk factors (e.g. CD4 cell nadir, current CD4 count, co-morbidities) for severe 
COVID-19 outcomes within the group of PLWHIV. 
3.2 Secondary objectives 
1. To describe differences in the clinical manifestation of COVID-19 in PLWHIV as compared to 
HIV seronegative controls. 
2. Describe, where appropriate, the response to treatment, including supportive care and 
novel therapeutics against COVID-19, including antiviral and immunomodulatory therapies 
3. To describe the co-morbidities in PLWHIV and controls with COVID-19 
4. To compare the COVID-19 severity in PLWHIV and controls at diagnosis and hospital 
admission.  
3.3 Primary endpoint/outcome 
 
1. The primary endpoint is a composite of: Critical care admission (high dependency unit or 
intensive care unit), mortality in hospital or palliative discharge when discharged from 
hospital, or mortality at 6 weeks after diagnosis of COVID-19 or at discharge from hospital 
(where applicable) 

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3.4 Secondary endpoints/outcomes 
 
1. Hospitalisation for COVID-19 
2. Length of stay in hospital 
3. Length of stay on ICU 
4. Number of ventilator-free days (VFDs) 
5. Length of extracorporeal membrane oxygenation (ECMO) 
6. Need for kidney replacement therapy 
7. Measurement of total comorbidity burden using the Charlson Comorbidity Index (CCI) and 
age-adjusted CCI (ACCI) 
8. Estimate risk of 30-day mortality after COVID-19 infection using pre-COVID health status 
(estimated using the Veterans Health Administration COVID-19 (VACO) index) 
9. Inflammatory marker and blood cell counts at COVID-19 diagnosis 
 
4 STUDY DESIGN 
 
This is an observational, retrospective, case-control study.  
4.1 Study Schema 
 
 
Figure 1: Study design with cases (PLWHIV & COVID-19) and two matched control groups. 
In total, 500 cases and up to 2500 controls will be analysed.  
Only real-world retrospective data will be used for this study. Deidentified retrospective data will be 
transcribed into the eCRF system from source data at each clinical site or from existing COVID-19 
cohort databases, where appropriate.  
 
For comparing PLWHIV & COVID-19 versus HIV seronegative COVID-19 patients, a 1:1 and 1:3 
matching will be performed according to the following criteria:  
• 
Age (+/- 5 years) 
• 
Sex 
• 
Ethnicity (where available) 
• 
Month of COVID-19 diagnosis (+/- 2 months) 
• 
COVID-19 diagnosis inpatient, 1:1 matching 
OR 
• 
COVID-19 diagnosis outpatient (ambulatory), 1:3 matching 

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For comparing PLWHIV & COVID-19 versus PLWHIV without COVID-19, a 1:2 matching for similar risk 
of acquiring COVID-19 will be performed according to the following criteria:  
• 
Age (+/- 5 years) 
• 
Sex 
• 
Ethnicity (where available) 
5 ELIGIBILITY CRITERIA 
The study population will consist of adult PLWHIV with and without COVID-19 disease and followed 
up at the study sites for routine clinical care. In addition, data from adult COVID-19 patients without 
HIV infection will be used as controls. 
Cases (PLWHIV + COVID-19) will be at least 18 years of age with documented HIV-1 infection and 
confirmed SARS-CoV-2 infection by documented, or patient-reported, positive result on PCR testing 
of a nasopharyngeal or respiratory sample, before 1st April 2021.  
Controls (COVID-19) will be at least 18 years of age without documented HIV-1 infection but confirmed 
SARS-CoV-2 infection by documented, or patient-reported, positive result on PCR testing of a 
nasopharyngeal or respiratory sample, before 1st April 2021.  
The second control group (PLWHIV) will include individuals at least 18 years of age with documented 
HIV-1 infection. 
5.1 Inclusion Criteria 
• 
Cases (PLWHIV + COVID-19) 
o Any gender 
o At least 18 years of age 
o Documented HIV-1 infection  
o Confirmed SARS-CoV-2 infection by documented, or patient-reported, positive result 
on PCR testing of a nasopharyngeal or respiratory sample, before 1st April 2021 
Each case should be matched to a control (1:1 or 1:3 respectively for COVID-19 controls and 1:2 for 
PLWHIV controls) according to the matching criteria set out in section 4.1. 
• 
Controls (COVID-19)  
o Any gender 
o At least 18 years of age  
o No documented HIV-1 infection 
o Confirmed SARS-CoV-2 infection by documented, or patient-reported, positive result 
on PCR testing of a nasopharyngeal or respiratory sample, before 1st April 2021 
o Meet the matching criteria 
• 
Controls (PLWHIV)  
o Any gender 
o At least 18 years of age  

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o Documented HIV-1 infection 
o No evidence of SARS-CoV-2 infection  
o Meet the matching criteria 
5.2 Exclusion Criteria 
• 
COVID-19 diagnosed based on clinical criteria 
 
6 STUDY PROCEDURES  
 
6.1 Subject Identification 
 
Most PLWHIV will be identified from sites in the NEAT ID network. PLWHIV are routinely followed-up 
at specialised outpatient clinics with regular follow up visits as standard of care. 
 
Since March 2020, more than 50 European sites have registered and started to provide basic 
information about the number of PLWHIV with COVID-19 and disease outcomes at their centres 
(https://www.NEAT-ID.org/). The dashboard provides a first estimate about the total numbers of 
PLWHIV with COVID-19 and where these patients are in continued care. As of 26th April 2021, 1,187 
PLWHIV with COVID-19 were reported in care across Europe, with 436 hospitalisations and 78 deaths 
from an estimated number of 85,279 PLWHIV in routine care at these sites. These case numbers 
strongly suggest feasibility to recruit sufficient numbers of PLWHIV with COVID-19 and that patients 
have been identified at their centres already. 
6.2 Data collection 
 
Only real-world retrospective data will be used for this study. Deidentified retrospective data will be 
transcribed into the eCRF system from source data at each clinical site or from existing COVID-19 
cohort databases, where appropriate. No personal identifiable data will be transmitted to NEAT ID. 
The data elements will be transcribed from source data according to the data collection list below. 
Mechanisms to ensure data quality and integrity will be deployed as per applicable standard operating 
procedures and in line with GCP and GPP. Patients and controls will be identified and documented by 
participating sites, provided unbiased matching for inpatient/outpatient status at the time of COVID-
19 diagnosis is ensured. Alternatively, and to avoid potential site-related bias during selection of HIV 
negative controls with COVID-19 diagnosed in hospital, data from matched controls will be obtained 
from appropriate existing COVID-19 cohort databases, e.g. LEOSS (Lean European Open Survey on 
SARS-CoV‑2 infected patients) or ISARIC (International Severe Acute Respiratory and emerging 
Infection Consortium). 
 
For all patients the following information will be collected: 
• 
Age  
• 
Sex 
• 
Ethnicity (where available) 
• 
Comorbidities (see appendix 1) 
• 
Weight (kg) and height (m) (to calculate BMI) 

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For patients with COVID-19 the following information will be collected (where applicable): 
• 
Date of positive PCR test result (documented or patient-reported) 
• 
COVID-19 diagnosis inpatient or outpatient 
• 
All-cause mortality in hospital, or palliative discharge, or mortality at 6 weeks after diagnosis 
of COVID-19 or at discharge from hospital 
• 
Hospitalisation for COVID-19 and length of hospitalisation 
• 
Critical care admission (high dependency unit or intensive care unit) for COVID-19 and length 
of stay in critical care 
• 
Length of invasive ventilation 
• 
Length of extracorporeal membrane oxygenation (ECMO)  
• 
Need for kidney replacement therapy 
• 
Inflammatory markers and blood cell counts at COVID-19 diagnosis1 (if available): 
o Full blood cell count (Platelet count, RBC Count, WBC count (absolute), 
Haemoglobin, Haematocrit, MCV, MCH, Neutrophils, Lymphocytes, Monocytes, 
Eosinophils, and Basophils), ALT, AST, total bilirubin, urea, serum creatinine, calcium, 
glucose and HbA1C levels, total cholesterol, triglycerides, CRP, D-dimer, ferritin, and 
lactate dehyrodgenase  
• 
Drug treatment for COVID-19 (glucocorticoids, azithromycin, remdesivir, monoclonal 
antibodies against SARS-CoV2, reconvalescent plasma, anti-IL1 inhibitors, anti-IL6 inhibitors, 
lopinavir/ritonavir, and others) 
 
For PLWHIV the following information will be collected: 
• 
Date of HIV diagnosis 
• 
Current ART 
• 
CDC disease stage 
• 
CD4 cell nadir 
• 
Last CD4 cell count (including CD4% and CD4/CD8 ratio) and HIV-RNA before COVID-19 
diagnosis, or most recent for HIV-only controls 
 
7 STATISTICS AND DATA ANALYSIS 
 
7.1 Sample size calculation 
 
The US Veterans Ageing Cohort Study (VACS) reported at AIDS 2020 [20] that the estimated proportion 
of non-HIV-infected individuals hospitalized with COVID-19 was 35%, 15% in ICU, 8% with invasive 
mechanical ventilation and 11% died. We anticipate a 1.1 to 2-fold increase in hazard rate in PLWHIV & 
COVID-19 (cases) relative to HIV-negative & COVID-19 (controls). With 500 cases and 1500  controls, a 
two-sided log-rank test at an alpha level of 0.05 will achieve at least 80% power to detect a 1.3-fold 
increase in the hazard rate of hospitalization, 1.4 for ICU, 1.6 for invasive mechanical ventilation and 1.5 
for death (refer to Table 1 below). The power calculation was made using the statistical software package 
nQuery Advanced, with the two samples Log-Rank test module (Version 8.6.1.0). 
 
Table 1 
 
1 Most recent available after positive SARS-CoV-2 PCR test, up to 10 days after positive test 

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Cases (PLWHIV & COVID-19, N=500);  
Controls (HIV-negative & COVID-19, N=up to 1500 )  
Alpha=5% (two-sided) 
Severity outcome 
Outcome (%) 
Power (%) 
Hazard Risk 
 
1.1 
1.2 
1.3 
1.4 
1.5 
1.6 
1.7 
1.8 
1.9 
2.0 
Hospitalization  
35 
20 
60 
90 
99 
>99 
>99 
>99 
>99 
>99 
>99 
ICU 
15 
11 
31 
58 
81 
94 
99 
>99 
>99 
>99 
>99 
Invasive mechanical ventilation 
8 
8 
19 
35 
54 
73 
86 
94 
98 
99 
>99 
Death 
11 
9 
24 
46 
68 
85 
95 
98 
>99 
>99 
>99 
 
For the search for factors associated with SARS-CoV-2 infection in PLWHIV, the recommended rule of 
thumb for sample size estimation for multivariable logistic regression models was n = 100 + 50i where i 
refers to number of independent variables in the final model [34]. With 1500 PLWHIV (500 with COVID-
19 and 1500 controls without COVID-19), we would be able to study 28 parameters with sufficient power 
to produce statistics that are nearly representative of the true values in the targeted population. 
However, sample size less than 1500 may be sufficient for associations that yield medium to large effect 
size. 
7.2 Planned recruitment rate 
 
We believe that approximately 30 European sites could participate. Therefore, we estimate that about 
60-80 patients would need to be recruited per site to reach the total number of subjects required. 
7.3 Statistical analysis plan 
 
The statistical hypotheses are: 1) to show whether HIV infection is associated with severe COVID-19 
compared to HIV uninfected individuals; 2) and to identify factors associated with severe COVID-19 
within HIV infected population. All eligible subjects with a matching individual will be included in the 
analysis population (full population analysis).  
 
Time-to-event methods, including Kaplan–Meier survival curves and Cox proportional-hazards 
models, will be used to compare PLWHIV with COVID-19 versus HIV seronegative COVID-19 controls 
for the severity of COVID-19 using parameters collected and adjusted for potential confounders. 
Conditional logistic regression models will be used to assess factors associated with COVID-19 within 
the group of PLWHIV to account for the case-control matching. 
7.3.1 
Summary of baseline data and flow of patients 
 
All continuous variables will be summarised using the following descriptive statistics: n (non-missing 
sample size), mean, standard deviation (SD), 1st quartile, median, 3rd quartile, maximum and 
minimum. The frequency and percentages (based on the non-missing sample size) of observed levels 
will be reported for all categorical variables. The number of patients and the flowchart of the study 
will be presented.  

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7.3.2 
Primary outcome analysis 
 
The first primary outcome analysis will be performed on PLWHIV with COVID-19 versus HIV uninfected 
individuals with COVID-19. The endpoint is the occurrence of critical care admission (high dependency 
unit or intensive care unit), mortality in hospital or palliative discharge when discharged from hospital, 
or mortality at 6 weeks after diagnosis of COVID-19 or at discharge from hospital (where applicable). 
Kaplan-Meier estimates will be used to estimate the proportion of participants with the primary 
endpoint events. Unadjusted and adjusted hazard ratios (HR) will be estimated using the Cox 
proportional hazard model to assess the impact of HIV-infection on the severity of COVID-19. The 
validity of the proportionality assumption will be assessed and tested. The adjusted variables will be 
the following (potential confounders): Age (<60 vs 60-64 vs 65-69 vs 70-74 vs ≥75 years); Sex at birth 
(female vs male); Obesity (BMI>30 kg/m2); and Comorbidities (see appendix 1). 
The second primary outcome analysis will be performed within the group of PLWHIV (PLWHIV with 
COVID-19 versus PLWHIV without COVID-19). The endpoint is to assess factors associated with severe 
COVID-19 within the group of PLWHIV. Conditional logistic regression models will be used to account 
for the case-control matching. The following variables will be assessed: Age (<60 vs 60-64 vs 65-69 vs 
70-74 vs ≥75 years); Sex at birth (female vs male); Obesity (BMI >30 kg/m2); Comorbidities (see 
appendix 1); time since HIV diagnosis (years); current ART; CDC disease stage; CD4 cell nadir; last CD4 
cell count/HIV-RNA before COVID-19 diagnosis (including CD4% and CD4/CD8 ratio) at baseline. For 
continuous variables, the decision to treat the variable as a continuous or categorical variable (as 
tertile) will be based on the lowest Akaike information criterion value for the corresponding 
univariable conditional logistic regression analysis. Variables achieving P < 0.20 in the univariable 
analysis will be retained for the multivariable analysis. 
7.3.3 
Secondary outcome analysis 
 
All secondary outcome analysis will be performed on PLWHIV with COVID-19 compared to HIV 
uninfected individuals with COVID-19. 
The proportion of hospitalised patients for COVID-19, the length of stay in hospital, the length of stay 
on ICU, the length of extracorporeal membrane oxygenation (ECMO), and the proportion of 
participants with a need for kidney replacement therapy will be estimated using the Kaplan-Meier 
estimate. Unadjusted and adjusted hazard ratios (HR) will be estimated using the Cox proportional 
hazard model to assess the impact of HIV-infection on the severity of COVID-19. The adjusted variables 
will be the same as those used for the first primary outcome analysis. 
The number of ventilator-free days (VFDs) will be compared between groups using competing risk 
regression, with extubation and mortality a competing event, adjusted for potential confounders. 
Linear regression models will be used to compare Charlson Comorbidity Index (CCI), the age-adjusted 
CCI (ACCI), 30-day mortality index after COVID infection, inflammatory marker and blood cell counts 
at COVID-19 diagnosis between the 2 groups, adjusted for potential confounders. The sample size will 
be quite large to consider CCI, 30-day mortality index, inflammatory marker and blood cell counts as 
normally distributed variables. 
7.4 Subject population 
 
All eligible subjects with a matching individual will be included in the analysis population (full 
population analysis). 

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7.5 Procedure(s) to account for missing or spurious data  
 
Multiple imputation using Chained Equations approach (MICE) will be used to fill in missing data. Ten 
imputations (M=10) will be chosen to obtain valid inference and reduce sampling variability resulting 
from the imputation process. Variables with a missing rate above 15% will be excluded and the 
outcomes will be included in the imputation model. All 10 datasets will be analyzed and combined 
using Rubin rules. 
 
8 DATA HANDLING 
8.1 Dissemination of results, authorship eligibility guidelines and any intended use of professional 
writers 
 
Data from the study will be published independently by NEAT ID. All contributing PI investigators will 
have the opportunity to participate in publication (abstracts and manuscripts) on the analyses.  
 
This study will be reported in line with the STROBE Statement for reporting observational studies. 
Details of this study and the results will be available on a freely accessible clinical trial registry 
(ISRCTN, clinicaltrials.gov or equivalent) and will be presented/disseminated at appropriate 
conferences. 
 
8.2 Data Protection 
 
Personal Data means any information relating to an identified or identifiable natural person (Data 
Participant), including without limitation pseudonymised information, as defined in the Applicable 
Law. The Applicable Law includes the Regulation (EU) 2016/679, its UK counterpart (UK GDPR) and 
other relevant regulations. Personal Data will only be collected in line with the study objectives as 
descried in this protocol, and to safeguard participants’ rights, only relevant, adequate, limited and 
necessary data will be collected and used. It is the Data Controller’s (the sponsor) responsibility to 
ensure compliance with the Applicable Law of a data processor (a CRO or an investigator site). 
 
Data processor(s) to aid the Controller with the Applicable Law compliance, must ensure that persons 
authorised to process the data, have committed themselves to confidentiality or are under an 
appropriate statutory obligation of confidentiality. Transfer of data must be strictly necessary for the 
implementation of the research or the use of the results. Transfers of data to a third country will be 
carried out in line with the applicable law and/or provisions ensuring adequacy (e.g.  Standard 
Contractual Clauses for the transfer of personal data).  
 
Data participant rights are upheld according to the applicable law. If a consent has been given, that 
consent may be withdrawn at any time. The withdrawal will not affect the lawfulness of the processing 
carried out prior. The personal data may continue to be processed where there is an appropriate legal 
basis for such processing. Rights to access, change or move of the collected information are limited as 

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the information must be managed in specific ways for the research to be reliable and accurate.  
 
8.3 Data Retention 
 
Patient data may be retained for up to two (2) years after the last publication of the results of research 
or, in the absence of publication, until the signing of the final research report.  
 
The personal data of professionals involved in research cannot be kept beyond a period of fifteen 
years (or in accordance with the current regulations) after the end of the last research in which they 
participated. 
 
 
9 ETHICAL AND REGULATORY CONSIDERATIONS 
9.1 Research Ethics Committee (REC) review & reports 
 
• 
Before the start of the trial, approval will be sought from a REC and/or any other 
applicable bodies for the trial protocol and other relevant documents  
• 
Where applicable a notification will be submitted to a Competent Authority in accordance 
with the country regulations 
• 
Substantial amendments that require review by REC will not be implemented until the 
REC grants a favourable opinion for the study (note that amendments may also need to 
be reviewed and accepted by the Competent Authority and/or local R&D departments 
before they can be implemented in practice at sites) 
• 
All correspondence with respect to submissions and approvals will be retained in the Trial 
Master File/Investigator Site File  
• 
An annual progress report (APR) will be submitted to the REC(s) within 30 days of the end 
of the reporting period, and annually until the trial is declared ended 
• 
It is the Chief Investigator’s responsibility to produce the annual reports as required. 
• 
The Chief Investigator will notify the REC(s) of the end of the study 
• 
If the study is ended prematurely, the Chief Investigator will notify the REC(s), including 
the reasons for the premature termination 
• 
Within one year after the end of the study, the Chief Investigator will submit a final report 
with the results, including any publications/abstracts, to the REC(s) 
9.2 Peer review 
 
This protocol has undergone peer review as per NEAT ID’s standard peer review process.  
 

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10 REFERENCES 
 
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S2352-3018(20)30111-9. 
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Mueller MC, Müller M, Römer K, Schewe K, Hoffmann C. COVID-19 in people living with human 
immunodeficiency virus: a case series of 33 patients. Infection. 2020 May 11. Doi: 10.1007/s15010-
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Jones S, Rahimian J. Outcomes among HIV-positive patients hospitalized with COVID-19 medRxiv 
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antibody response in a case of COVID-19 with a history of co-infection with HIV-1 and HCV. Clin 
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Hannongbua S, Rungrotmongkol T. Why Are Lopinavir and Ritonavir Effective against the Newly 
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Persons Receiving Antiretroviral Therapy: A Cohort Study [published online ahead of print, 2020 Jun 
26]. Ann Intern Med. 2020;10.7326/M20-3689.9.  
8. 
Martinez MA. Compounds with Therapeutic Potential against Novel Respiratory 2019 
Coronavirus. Antimicrob Agents Chemother. 2020 Apr 21;64(5). Pii: e00399-20. 
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Ford N, Vitoria M, Rangaraj A, Norris SL, Calmy A, Doherty M. Systematic review of the 
efficacy and safety of antiretroviral drugs against SARS, MERS or COVID-19: initial assessment. J Int 
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10. 
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Districts of Wuhan, China. Preprint research paper, The Lancet, 2020. 
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Wu Q, Chen T, Zhang H. Recovery from COVID-19 in two patients with coexisted HIV 
infection. J Med Virol. 2020 May 13. Doi: 10.1002/jmv.26006. [Epub ahead of print] 
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Karmen-Tuohy S, Carlucci PM, Zacharioudakis IM, Zervou FN, Rebick G, Klein E, Reich J, Jones 
S, Rahimian J. Outcomes among HIV-positive patients hospitalized with COVID-19. medRxiv. A  
https://www.medrxiv.org/content/10.1101/2020.05.07.20094797v1 (This preprint report has not 
been peer-reviewed.) 
13. 
Gervasoni C, Meraviglia P, Riva A, Giacomelli A, Oreni L, Minisci D, Atzori C, Ridolfo A, 
Cattaneo D. Clinical features and outcomes of HIV patients with coronavirus disease 2019. Clin Infect 
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Shalev N, Scherer M, LaSota ED, et al. Clinical characteristics and outcomes in people living 
with HIV hospitalized for COVID-19 [published online ahead of print, 2020 May 30]. Clin Infect Dis. 
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Suwanwongse K, Shabarek N. Clinical features and outcome of HIV/SARS-CoV-2 coinfected 
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Vizcarra P, Pérez-Elías MJ, Quereda C, et al. Description of COVID-19 in HIV-infected 
individuals: a single-centre, prospective cohort [published online ahead of print, 2020 May 28]. 
Lancet HIV. 2020;S2352-3018(20)30164-8. 
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Ridgway JP, Schmitt J, Friedman E, et al. HIV Care Continuum and COVID-19 Outcomes 
Among People Living with HIV During the COVID-19 Pandemic, Chicago, IL [published online ahead of 
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Patel VV, et al. Clinical outcomes by HIV serostatus, CD4 count, and viral suppression among 
people hospitalized with COVID-19 in the Bronx, New York. AIDS 2020: Virtual; July 6-10, 2020. Abst.  
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Park LS, et al. COVID-19 in the largest US HIV cohort. AIDS 2020: Virtual; July 6-10, 2020. 
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Lee MJ, et al. Comparative outcomes in hospital admissions with COVID-19 in people living 
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Geretti AM et al, BHIVA Virtual Conference, 3rd July 2020. 
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Davies MA et al. COVID-19 mortality in people with HIV or tuberculosis: Results from the 
Western Cape Province, South Africa. AIDS 2020: Virtual; July 6-10, 2020. Abst OAXLB0106 
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Wu C, Liu Y, Yang Y et al. Analysis of therapeutic targets for SARS-CoV-2 and discovery of 
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Jockusch S, Tao C, Li X, Anderson TK, Chien M, Kumar S, et al. Triphosphates of the Two 
Components in DESCOVY and TRUVADA are Inhibitors of the SARS-CoV-2 Polymerase. bioRxiv 2020; 
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Clososki GC et al. Tenofovir Disoproxil Fumarate: New Chemical Developments and 
Encouraging in vitro Biological results for SARS-CoV-2. J Braz Chem Soc 2020; 31: 1552-1556 a  
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Park SJ, Yu KM, Kim YI, et al. Antiviral efficacies of FDA-approved drugs against SARS-CoV-2 
infection in ferrets. mBio. 2020;11. [PMID: 32444382] doi:10.1128/mBio.01114-20  
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Choy K-T, Wong AY-L, Kaewpreedee P, Sia SF, Chen D, Hui KPY, Chu DKW, Chan MCW, 
Cheung PP-H, Huang X, Peiris M, Yen H-L. 2020. Remdesivir, lopinavir, emetine, and 
homoharringtonine inhibit SARS-CoV-2 replication in vitro. Antiviral Res 178:104786. 
30. 
Xie X, Muruato AE, Zhang X et al. A nanoluciferase SARS-CoV-2 for rapid neutralization 
testing and screening of anti-infective drugs for COVID-19. bioRxiv 2020.06.22.165712; doi: 
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hospitalised-covid-19-patients-studied-in-recovery; accessed 20th July 2020. 
33. 
Riva A, Conti F, Bernacchia D, et al. Darunavir does not prevent SARS-CoV-2 infection in HIV 
patients. Pharmacol Res. 2020 Jul; 157: 104826. Published online 2020 Apr 20. Doi: 
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Bujang MA, Sa’at N, Sidik TMITAB, Joo LC. Sample Size Guidelines for Logistic Regression 
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11 APPENDICIES 
 
APPENDIX 1 – Comorbidity Variables & Definitions 
 
VARIABLE 
DEFINITION 
Myocardial Infarction (heart attack) 
History of definite or probable MI (EKG changes and/or 
enzyme changes) 
Congestive Heart Failure 
Exertional or paroxysmal nocturnal dyspnoea and has 
responded to digitalis, diuretics, or afterload reducing 
agents 
Peripheral Vascular Disease 
Intermittent claudication or past bypass for chronic arterial 
insufficiency, history of gangrene or acute arterial 
insufficiency, or untreated thoracic or abdominal 
aneurysm (≥6 cm) 
Cerebrovascular Accident (stroke) or 
Transient Ischemic Attack 
History of a cerebrovascular accident with minor or no 
residua and transient ischemic attacks 
Dementia 
Chronic cognitive deficit 
Chronic Obstructive Pulmonary 
Disease 
- 
History of Pneumonia 
- 
Connective Tissue Disease 
• 
Rheumatologic Disease 
• 
Any Other 
- 
Peptic Ulcer Disease 
Any history of treatment for peptic ulcer disease or history 
of peptic ulcer bleeding 
Liver Disease 
• 
Mild 
• 
Moderate 
• 
Severe 
Mild = chronic hepatitis (or cirrhosis without portal 
hypertension) 
Moderate = cirrhosis and portal hypertension but no 
variceal bleeding history 
Severe = cirrhosis and portal hypertension with variceal 
bleeding history 
Diabetes 
• 
None or Diet-Controlled 
• 
Uncomplicated 
• 
With Complications 
- 
Hemiplegia 
- 
Paralysis of Arm(s) or Leg(s) 
- 
Chronic Kidney Disease 
• 
Moderate 
Moderate = creatinine >3 mg/dL (0.27 mmol/L) 
Severe = on dialysis, status post kidney transplant, uraemia 

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• 
Severe 
Current or History of Cancer 
• 
Localised 
• 
Metastatic 
- 
Leukaemia 
- 
Lymphoma 
- 
AIDS 
- 
 
 

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APPENDIX 2 – Amendment History 
 
Amendment 
No. 
Protocol 
version no. 
Date issued 
Author(s) of 
changes 
Details of changes made 
N/A 
1.0 
28June2021 
Prof Georg Behrens, 
CI 
Jacob Lowman, 
Clinical Project 
Manager 
Initial version 
01 
2.0 
10NOV2021 
Prof Georg Behrens, 
CI 
Jacob Lowman, 
Clinical Project 
Manager 
Addition of inclusion criteria 
for COVID-19 diagnosis 
confirmed before 1st April 
2021 only. 
Addition of matching criteria 
for COVID-19 diagnosis 
inpatient or outpatient. 
Addition of wording to allow 
for flexibility in use of 
existing COVID-19 cohort 
databases. 
02 
Draft 2.1  
29AUG2022 
Prof Georg Behrens, 
CI 
Kathryn Fellows, 
Clinical Project 
Manager 
Addition of COVID-19 only 
controls to be increased up 
to 1500  
Addition of wording to allow 
for 1:3 matching on COVID-
19 only data.  
 
 
 

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