malariaAtlas: an R interface to global malariometric data hosted by the Malaria Atlas Project

Pfeffer, Daniel; Lucas, Timothy C. D.; May, D.; Harris, Jonathan; Rozier, Jennifer; Twohig, Katherine A.; Dalrymple, Ursula; Guerra, Carlos A.; Moyes, Catherine L.; Thorn, Mike; Nguyen, Michele; Bhatt, Samir; Cameron, Ewan; Weiss, Daniel J.; Howes, Rosalind E.; Battle, Katherine E.; Gibson, Harry S.; Gething, Peter W.

doi:10.1186/s12936-018-2500-5

Cited by 91 publications

(96 citation statements)

References 35 publications

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“…Curves of recent historical effective population size were estimated from between-isolate IBD segments with 'IBDNe' v07May18-6a4 [29] using length threshold > 3 cM, 20 bootstrap replicates and default parameters otherwise. Local age-adjusted parasite prevalence point estimates (PfPR 2-10 ) and credible intervals were obtained from the Malaria Atlas Project [30] via the R package 'malariaAtlas' [31].…”

Section: Demographic Inferencementioning

confidence: 99%

Falciparum malaria from coastal Tanzania and Zanzibar remains highly connected despite effective control efforts on the archipelago

Morgan

Brazeau

Ngasala

et al. 2020

Malar J

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Background: Tanzania's Zanzibar archipelago has made significant gains in malaria control over the last decade and is a target for malaria elimination. Despite consistent implementation of effective tools since 2002, elimination has not been achieved. Importation of parasites from outside of the archipelago is thought to be an important cause of malaria's persistence, but this paradigm has not been studied using modern genetic tools. Methods: Whole-genome sequencing (WGS) was used to investigate the impact of importation, employing population genetic analyses of Plasmodium falciparum isolates from both the archipelago and mainland Tanzania. Ancestry, levels of genetic diversity and differentiation, patterns of relatedness, and patterns of selection between these two populations were assessed by leveraging recent advances in deconvolution of genomes from polyclonal malaria infections. Results: Significant decreases in the effective population sizes were inferred in both populations that coincide with a period of decreasing malaria transmission in Tanzania. Identity by descent analysis showed that parasites in the two populations shared long segments of their genomes, on the order of 5 cM, suggesting shared ancestry within the last 10 generations. Even with limited sampling, two of isolates between the mainland and Zanzibar were identified that are related at the expected level of half-siblings, consistent with recent importation. Conclusions: These findings suggest that importation plays an important role for malaria incidence on Zanzibar and demonstrate the value of genomic approaches for identifying corridors of parasite movement to the island.

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Section: Demographic Inferencementioning

confidence: 99%

Falciparum malaria from coastal Tanzania and Zanzibar remains highly connected despite effective control efforts on the archipelago

Morgan

Brazeau

Ngasala

et al. 2020

Malar J

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“…The epidemiology module is parameterized with typical parameter values for Plasmodium falciparum transmission (Table S1), human population size and life expectancy parameters from the National Institute of Statistics and Demographic Studies, Comoros (INSEED, 2015), and is calibrated to local malaria prevalence estimates from the Malaria Atlas Project (Pfeffer et al , 2018). This calibration was achieved by multiplying the carrying capacity time series by a constant such that the average adult female mosquito population over a year sustained malaria transmission in the human population at the estimated local prevalence.…”

Section: Resultsmentioning

confidence: 99%

MGDrivE 2: A simulation framework for gene drive systems incorporating seasonality and epidemiological dynamics

Wu¹,

Bennett²,

C.³

et al. 2020

Preprint

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Interest in gene drive technology has continued to grow as promising new drive systems have been developed in the lab and discussions are moving towards implementing field trials. The prospect of field trials requires models that incorporate a significant degree of ecological detail, including parameters that change over time in response to environmental data such as temperature and rainfall, leading to seasonal patterns in mosquito population density. Epidemiological outcomes are also of growing importance, as: i) the suitability of a gene drive construct for release will depend on its expected impact on disease transmission, and ii) initial field trials are expected to have a measured entomological outcome and a modeled epidemiological outcome. We present MGDrivE 2 (Mosquito Gene Drive Explorer 2): an extension of and development from the MGDrivE 1 simulation framework that investigates the population dynamics of a variety of gene drive architectures and their spread through spatially-explicit mosquito populations. Key strengths and improvements of the MGDrivE 2 framework are: i) the ability of parameters to vary with time and induce seasonal population dynamics, ii) an epidemiological module accommodating reciprocal pathogen transmission between humans and mosquitoes, and iii) an implementation framework based on stochastic Petri nets that enables efficient model formulation and flexible implementation. Example MGDrivE 2 simulations are presented to demonstrate the application of the framework to a CRISPR-based homing gene drive system intended to drive a disease-refractory gene into a population, incorporating time-varying temperature and rainfall data, and predict impact on human disease incidence and prevalence. Further documentation and use examples are provided in vignettes at the project's CRAN repository. MGDrivE 2 is an open-source R package freely available on CRAN. We intend the package to provide a flexible tool capable of modeling gene drive constructs as they move closer to field application and to infer their expected impact on disease transmission.

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“…To validate our models, we tested if S(T ) is consistent with data on observed malaria prevalence in Africa and Asia, using generalized linear models (GLMs). We obtained data on P. falciparum and P. vivax prevalence data collected at the village level in 46 countries in Africa and 21 countries in Asia from 1990 to 2017 from the Malaria Atlas Project (Pfeffer et al, 2018). The prevalence data were matched with monthly aggregated mean temperature data for the quarter prior to the start month of each study obtained from the WorldClim Global Climate Data Project (Fick and Hijmans, 2017) using latitude and longitude coordinates as merging points.…”

Section: Model Validationmentioning

confidence: 99%

Temperature impacts the transmission of malaria parasites byAnopheles gambiaeandAnopheles stephensimosquitoes

Villena

Ryan

Murdock

et al. 2020

Preprint

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Transmission of malaria and other vector-borne diseases (VBDs) is greatly influenced by environmental factors, especially temperature, due to the ectothermic nature of insect and arthropod vectors. However, the response of transmission to temperature and other drivers is complex, as thermal traits of ectotherms are typically non-linear, and they interact to determine transmission constraints. In this study, we assess and compare the effect of temperature on the transmission of two malaria parasites, Plasmodium falciparum and Plasmodium vivax, by two malaria vector species, Anopheles gambiae and Anopheles stephensi. We model the non-linear responses of temperature dependent mosquito and parasite traits (mosquito development rate, bite rate, fecundity, egg to adult survival, vector competence, mortality rate, and parasite development rate) and incorporate these traits into a suitability metric based on a model for the basic reproductive number across temperatures. Our model predicts that the optimum temperature for transmission suitability is similar for the four mosquito-parasite combinations assessed in this study. The main differences are found at the thermal limits. More specifically, we found significant differences in the upper thermal limit between parasites spread by the same mosquito (An. stephensi) and between mosquitoes carrying P. falciparum. In contrast, at the lower thermal limit the significant differences were primarily between the mosquito species that both carried the same pathogen (e.g., An. stephensi and An. gambiae both with P. falciparum). Using prevalence data from Africa and Asia, we show that the transmission suitability metric S(T) calculated from our mechanistic model is an important predictor of malaria prevalence. We mapped risk to illustrate the areas in Africa and Asia that are suitable for malaria transmission year-round based temperature. The wider thermal range of transmission by An. stephensi for both malaria parasites allows for a greater geographic potential for malaria spread. This study could be useful in planing preventive strategies for areas where malaria outbreaks might occur.

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malariaAtlas: an R interface to global malariometric data hosted by the Malaria Atlas Project

Cited by 91 publications

References 35 publications

Falciparum malaria from coastal Tanzania and Zanzibar remains highly connected despite effective control efforts on the archipelago

Falciparum malaria from coastal Tanzania and Zanzibar remains highly connected despite effective control efforts on the archipelago

MGDrivE 2: A simulation framework for gene drive systems incorporating seasonality and epidemiological dynamics

Temperature impacts the transmission of malaria parasites byAnopheles gambiaeandAnopheles stephensimosquitoes

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