Peer review of: Incorporating hydrology into climate suitability models changes projections of malaria (2020)

Reviewers' Comments: 
 
Reviewer #1: 
Remarks to the Author: 
Review of "Hydro-climatic suitability of malaria transmission in Africa: new patterns 
emerge" 
Manuscript number: NCOMMS-20-04720-T 
Authors: Smith et al., 2020 
Recommendation: Major revisions 
 
General: 
This study employs a novel malaria model that combines irrigation effects, temperature 
suitability curves and the LisFlood hydrological model in order to derive high resolution 
maps of malaria risk in Africa. Future projections are provided to investigate climate change 
effects. There is an excellent section comparing different published rainfall models and 
thresholds, and novel estimates of population at risk. Overall the paper is well written, the 
analysis and plots are neat and clear. The approach is quite novel and should be published 
in Nature communications. However, I have several major comments that need to be 
addressed before acceptance of the manuscript. I encourage the authors to address my 
comments. 
 
Major points: 
1] Modern estimate of malaria risk to add 
The authors provide pre-control map of malaria endemicity risk by Lysenko et al. As the 
model is driven by climate parameters it makes sense. I think the authors should provide 
recent risk maps of P. falciparum infections in Africa would be a plus. The authors could use 
simulated prevalence data from the Malaria Atlas project (data can be downloaded in the 
explorer - https://malariaatlas.org/) to discuss the recent context (and discrepancies with 
climate driven malaria models). 
2] Large malaria season values simulated over the Sahelian fringe 
One of my main concern, the Lisflood and Lisflood/irrigation model seems to overestimate 
the simulated length of the transmission season. In Senegal for example, clinical malaria 
cases tend to be reported in Oct-Nov-Dec (3 months roughly which fits the old Tanser 
model) with very few cases during the dry season. See the work by I. Diouf for example 
(https://doi.org/10.3390/ijerph14101119). Year-round transmission values in the Nile 
region must be backed up by medical papers / epidemiological studies as well. This 
overestimation appears clearly on Fig 2e-f where LisFlood predicts a very large surface 
suitable for 9-12 months. DRC values should be larger I think, this is one of the most 
endemic country in Africa. Basically, the authors should provide more details on these 
issues in discussion. 
3] Climate Model bias-correction? 
A few points here. Firstly, the authors should emphasize that they are using a Regional 
Climate Model driven by an ensemble of 7 GCMs in the abstract. Secondly, the authors 
should use a bias-calibration technique. RCM driven by GCM can show large temperature 
and rainfall biases over Africa. Consequently, this point needs to be addressed or at least 
mentioned as an important caveat in discussion. 

4] Malaria model description to be improved. 
First, I think the authors should find an acronym for their malaria model (as Lisflood is 
already a hydrological model?). The main model description in methods should be extended 
in Supp Materials. A diagram or schematic showing the different input layers (irrigation, 
population etc) and if they vary in space and/or time would be a good addition, or this 
information can also be included in a summary table. 
5] Other hydrological malaria models could be mentioned in Introduction 
I am thinking about the work by Arne Bomblies & Yamana et al. 
(https://doi.org/10.1029/2008WR006917 - 
https://malariajournal.biomedcentral.com/articles/10.1186/1475-2875-8-223 - 
https://www.nature.com/articles/nclimate3085). These other models developed for small 
scale applications should be compared to the main author’s findings as well. 
 
Minor points: 
Intro: “…malaria deaths were reported in Africa.” 
Intro: “… biting rates and individual longevity (add references)” 
Intro: “of both parasite and vectors”. Importantly the authors should investigate the recent 
work by Waite et al (https://doi.org/10.1098/rsbl.2019.0275) who showed lower 
temperature thresholds for sporogony in key Anopheles vectors. 
Intro: “The availability … of malaria transmission (add references to Bomblies and Yamana 
work)” 
Intro: “Moreover… not included in such models”. The authors could add a couple of 
sentences about potential dam effects on malaria, it’s a very important issue (see work by 
Solomon Kibret - https://malariajournal.biomedcentral.com/articles/10.1186/s12936-015-
0873-2). 
Page 7: “Lisflood projected percentage … Tanzania”. This sentence is poorly written, please 
reword 
Conclusion: “… could be attributed to climate alone”. The work by Gething et al. should also 
be cited here (https://www.nature.com/articles/nature09098) 
 
 
 
Reviewer #2: 
Remarks to the Author: 
Hydro-climatic suitability of malaria transmission in Africa: new patterns emerge  
 
This is a well-written paper that develops the science on malaria hazard. The authors show 
that the use of a hydrological model to map climatic suitability for malaria transmission 
produces a better match with the pre-intervention malaria map of Lysenko and Semashko. 
This is a nice result and provides confidence in their subsequent predictions of future 
climatic suitability. 
 
I have been asked to comment on the hydrological modelling specifically. I believe 
LISFLOOD is a good choice of model for this application, and my only slight query is with 
the use of the 30m3s-1 minimum threshold for suitability. In particular, the authors state 
that the area estimated to be hydro-climatically suitable for stable malaria transmission is 

smaller than previous models suggest. I wonder if this result stands if a different threshold 
is used. 
 
Firstly, for clarity, I would recommend that the authors cite the source of this threshold 
(Kiszewski et al.(2004)) within the main body of text (rather than just in the supplementary 
information), secondly, I would like to see a sensitivity analysis of this threshold (not 
necessarily in the main body of text, but definitely in the supplementary material). There is 
always a challenge in relating the real world to the model world, especially to models with a 
course spatial representation of hydrology. The suitability threshold should be seen as an 
effective parameter, in that it is used to attempt to represent suitable accumulations of 
water far smaller than the grid scale. Is the area still smaller than previous models suggest 
if different values for this suitability threshold are used? 
 
Liz Stephens 
 
 
 
Reviewer #3: 
Remarks to the Author: 
This study applies a continental-scale hydrologic model combined with malaria temperature 
suitability to produce a mapping of current and future climate suitability for malaria 
transmission. In theory, the addition of hydrological processes and irrigation should be an 
improvement over models that use rainfall alone as they would provide a more accurate 
measure of suitable breeding habitat for the Anopheles mosquitoes that transmit malaria. 
 
However, there is little validation of the model to prove that this is the case. Understandably 
– validation is challenging, as the authors note. The validation presented here consists of a 
visual comparison to the map of malaria transmission limits in 1900 constructed by Lysenko 
& Semashko by interpolating historical records with climate data and expert opinion. From 
Figure 2 of the paper, it is not obvious to me that the new model outperforms the Tanser 
model at reproducing the Lysenko map. From Figure S4, the model appears to do rather 
poorly at the northern and southern limits of malaria transmission, as well as in the East 
African highlands. This discrepancy is problematic, as these are precisely the areas that are 
most sensitive to changes in transmission potential due to climate change. 
 
Interestingly, the hydrological model presented here is also applied as a simple threshold 
rule (30 m3/s over a 0.5-degree grid cell). It is unclear how this threshold relates to the 
fine-scale hydrological processes that determine anopheles habitat availability, given the 
species’ preference for puddles and small water pools on the order of meters to tens of 
meters. 
 
While the inclusion of hydrology and irrigation are useful and there are some interesting 
results presented as far as climate change projections, I believe the model must first be 
more convincing in defining malaria suitability in the present climate before we can begin to 
consider its ability to make projections in a new climate. 
 

Specific comments: 
1. The model needs to be better validated. Comparison with the Lysenko map should be 
better quantified. Additional comparisons to higher quality data, for example malaria 
prevalence surveys such as those use by Tanser or anopheles occurrence surveys, would 
greatly improve the credibility of the model. The Malaria Atlas Project provides some such 
data on their website. 
 
2. The discrepancy at the northern and southern limits of climate suitability, as well as East 
Africa, should be addressed. 
 
3. The choice of the rainfall runoff threshold value should be discussed, and sensitivity to 
this value should be assessed. 
 
4. The discussion should mention the disconnect between the scale of 55km grid cell 
hydrologic modeling and finer-scale processes determining availability of anopheles 
breeding habitat. 
 
5. There should be mention of the work in the decade+ following Tanser and other simple 
threshold models that use hydrologic processes and/or mosquito larval biology in 
determining climate suitability for malaria 
 
6. This is more a matter of preference, but I believe there is too much emphasis in the 
manuscript on drawing comparisons between projections under Tanser’s formulation vs 
Lisflood – I don’t believe the Tanser projections are considered to be definitive or a 
consensus view. If a comparison to other maps or projections is necessary, there have been 
a number of more recent projections that may be more relevant.