Heterogeneous mosquito exposure increases Plasmodium vivax and Plasmodium falciparum coinfections: a modelling study
Data files
Oct 24, 2024 version files 13.54 KB
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README.md
5.62 KB
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Review_data.Rdata
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Abstract
In malaria-endemic regions, Plasmodium vivax and Plasmodium falciparum coexist and may interact. For instance, fevers induced by P. falciparum might activate dormant P. vivax parasites and concurrent radical cure of both species has been proposed to prevent relapses. Heterogeneous mosquito exposure may contribute to the dependence of both parasites. We conducted a literature review on their respective prevalence and that of coinfections. The data revealed a positive correlation between P. vivax and P. falciparum prevalence and coinfection prevalences exceeding expectations assuming infections occur independently. We used the review data to fit a compartmental model of coinfections that features heterogeneous mosquito exposure. The fit suggests that heterogeneous exposure sufficiently explains the observed departure from independence. Finally, we performed simulations under the model assessing the impact on P. vivax prevalence of the activation-by-fever hypothesis and the radical cure proposition. We demonstrated a moderate impact of allowing P. falciparum fevers to reactivate P. vivax and a substantial impact of treating P. falciparum cases with radical cure. Our model highlights the dependence between P. falciparum and P. vivax and emphasises the influence of heterogeneous mosquito exposure. This simple framework can inform the design of more complex models assessing integrated malaria control strategies in co-endemic regions.
https://doi.org/10.5061/dryad.k0p2ngfhq
Description of the data and file structure
The present repository includes data collected via a literature review of field studies recording P. vivax and P. falciparum infection, and coinfection prevalence. This data was used for:
- An analysis of the statistical dependence between P. vivax and P. falciparum infection prevalence
- Fitting a compartmental model of coinfections with P. vivax and P. falciparum
Files and variables
File: Review_data.Rdata
Description: This file contains the information extracted from each study included after the literature review.
Variables:
- method: The diagnostic method used for species identification in the included study.
- sample size: The number of samples evaluated in the included study.
- country of study site(s): The country in which study was the included study was performed.
- Pf_prev (%): The prevalence of P. falciparum single infections recorded in the included study.
- Pv_prev (%): The prevalence of P. vivax single infections recorded in the included study.
- Mixed_prev (%): The prevalence of P. falciparum and P. vivax mixed infections recorded in the included study.
- Pf_prev (%) all: The prevalence of all P. falciparum infections (single or mixed) recorded in the included study.
- Pv_prev (%) all: The prevalence of all P. vivax infections (single or mixed) recorded in the included study.
- All_prev (%): The prevalence of any Plasmodium infections (single or mixed) recorded in the included study.
- mixed/Pf_prev all: The ratio between the prevalence of mixed infections and the prevalence of all P. falciparum infections (single or mixed) recorded in the included study.
- mixed/Pv_prev all: The ratio between the prevalence of mixed infections and the prevalence of all P. vivax infections (single or mixed) recorded in the included study.
- mixed/PvPf_prev all: The ratio between the prevalence of mixed infections and the prevalence of any Plasmodium infections (single or mixed) recorded in the included study.
- Mixed_prev (%) exp: The prevalence of mixed infections expected from the prevalence of P. vivax infections (single or mixed) and of P. falciparum infections (single or mixed) recorded in the included study, i.e. the product of the prevalence of P. vivax infections (single or mixed) and of P. falciparum infections recorded in the included study.
- mixed_exp/Pf_prev all: The ratio between the expected prevalence of mixed infections (defined above) and the prevalence of all P. falciparum infections (single or mixed) recorded in the included study.
- mixed_exp/Pv_prev all: The ratio between the expected prevalence of mixed infections (defined above) and the prevalence of all P. vivax infections (single or mixed) recorded in the included study.
- mixed_exp/PvPf_prev: The ratio between the expected prevalence of mixed infections (defined above) and the prevalence of any Plasmodium infections (single or mixed) recorded in the included study.
- Region: The country where the included study was conducted, classified into ”Africa”, “Indian/Pacific Ocean”, “South America”, “South Asia”, or “South-East Asia”.
- method2: The diagnostic method used for species identification in the included study, classified as “PCR”, or “Other”.
- Sizes: The number of samples evaluated in the included study, scaled between 0 and 1 (for plotting purposes).
Code/software
The data analysis and model fitting were done in R version 4.4.1 (2024-06-14).
Necessary R-packages to run the code are deSolve, statmod, scales, and dplyr.
- Helper.R is a script containing helper functions and recurring parameters.
- Heterogeneity_model_coinfection.R is the script encoding the coinfection model under heterogeneous exposure to mosquito bites, which is presented in the article.
- Heterogeneity_febrile_trigger_model_coinfection.R is the script encoding the same model but allowing for febrile P. falciparum infections to trigger P. vivax hypnozoite reactivation (relapse).
- Heterogeneity_radical_cure_model_coinfection.Rs the script encoding the same model but allowing for blood-stage or radical cure treatment of P. falciparum and P. vivax.
- Null_model.R is the script encoding the model of coinfection under no heterogeneity.
- ABC_prior_sampling.R is a script sampling from parameter priors, which are plugged into the compartmental model to output equilibrium prevalences of P. vivax, P. falciparum and coinfection. This script outputs the R object sample.rds.
- ABC_nearest_neighbor.R is a script selecting the 100 nearest neighbors of each review data point among the prior sampled prevalence triplets. This script outputs the R object 5800_nearest_neighbors.rds.
- Het_febrile_trigger_simulations.R is the script running simulations under different scenarios of hypnozoite activation by P. falciparum fevers.
- Het_radical_cure_simulations.R is the script running scenario simulations of different blood-stage treatments or radical cure regimens.
- Identifyability.R is the script diagnosing issues with identifiability for the 3 fitted parameters.
- Sensitivity.R is the script of a sensitivity analysis around each of the assumed (not estimated) parameters.
We performed a literature review on PubMed to collect data from field epidemiology studies recording P. vivax, P. falciparum, and coinfection prevalence, among the general population. Specifically, we defined those studies as cross-sectional and active infection-detection studies performed in communities, unrestricted by age, sex, or symptomatic status. The keywords we used were:
Title: (Malaria OR Vivax OR Falciparum) NOT (Health-care facility OR Hospital OR Health centre OR Systematic Review OR Meta*)
Abstract: Prevalence OR Distribution OR Epidemiology OR Cross-section
Text: Vivax AND Falciparum
After title and abstract screening with “Rayyan”, we screened the main text and extracted the P. vivax, P. falciparum, and coinfection prevalence from each study, as well as the sample size and diagnostic method used to generate prevalence. We excluded studies that failed to report all those metrics or that did not screen the general population. A spreadsheet of the details of all the studies retained after title and abstract screening is available as a supplementary file.
We defined different metrics related to the coupled dynamics of P. vivax, P. falciparum, and coinfections. First, we introduced the notion of expected coinfection prevalence under the independence of P. vivax and P. falciparum. That is, we assumed that if P. vivax and P. falciparum transmission are independent, coinfection prevalence should be the product of P. falciparum and P. vivax prevalence. We then defined the proportional excess coinfection prevalence as the difference between observed and expected coinfection prevalence, normalized by different measures of local transmission intensity: P. vivax prevalence, P. falciparum prevalence, or overall malaria prevalence.