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1. Understanding Spatiotemporal Human Mobility Patterns for Malaria Control Using a Multiagent Mobility Simulation Model

   https://doi.org/10.1093/cid/ciac568  

   Li, Yao ; Stewart, Kathleen ; Han, Kay Thwe ; Han, Zay Yar ; Aung, Poe P. ; Thein, Zaw W. ; Htay, Thura ; Chen, Dong ; Nyunt, Myaing M. ; Plowe, Christopher V. ( July 2022 , Clinical Infectious Diseases)

   More details about human movement patterns are needed to evaluate relationships between daily travel and malaria risk at finer scales. A multiagent mobility simulation model was built to simulate the movements of villagers between home and their workplaces in 2 townships in Myanmar.

   An agent-based model (ABM) was built to simulate daily travel to and from work based on responses to a travel survey. Key elements for the ABM were land cover, travel time, travel mode, occupation, malaria prevalence, and a detailed road network. Most visited network segments for different occupations and for malaria-positive cases were extracted and compared. Data from a separate survey were used to validate the simulation.

   Mobility characteristics for different occupation groups showed that while certain patterns were shared among some groups, there were also patterns that were unique to an occupation group. Forest workers were estimated to be the most mobile occupation group, and also had the highest potential malaria exposure associated with their daily travel in Ann Township. In Singu Township, forest workers were not the most mobile group; however, they were estimated to visit regions that had higher prevalence of malaria infection over other occupation groups.

   Using an ABM to simulate daily travel generated mobility patterns for different occupation groups. These spatial patterns varied by occupation. Our simulation identified occupations at a higher risk of being exposed to malaria and where these exposures were more likely to occur.

    

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2. Mapping current and future thermal limits to suitability for malaria transmission by the invasive mosquito Anopheles stephensi

   https://doi.org/10.1186/s12936-023-04531-4  

   Ryan, Sadie J. ; Lippi, Catherine A. ; Villena, Oswaldo C. ; Singh, Aspen ; Murdock, Courtney C. ; Johnson, Leah R. ( March 2023 , Malaria Journal)

   Anopheles stephensiis a malaria-transmitting mosquito that has recently expanded from its primary range in Asia and the Middle East, to locations in Africa. This species is a competent vector of bothPlasmodium falciparumandPlasmodium vivaxmalaria. Perhaps most alarming, the characteristics ofAn.stephensi, such as container breeding and anthropophily, make it particularly adept at exploiting built environments in areas with no prior history of malaria risk.

   In this paper, global maps of thermal transmission suitability and people at risk (PAR) for malaria transmission byAn.stephensiwere created, under current and future climate. Temperature-dependent transmission suitability thresholds derived from recently published species-specific thermal curves were used to threshold gridded, monthly mean temperatures under current and future climatic conditions. These temperature driven transmission models were coupled with gridded population data for 2020 and 2050, under climate-matched scenarios for future outcomes, to compare with baseline predictions for 2020 populations.

   Using the Global Burden of Disease regions approach revealed that heterogenous regional increases and decreases in risk did not mask the overall pattern of massive increases of PAR for malaria transmission suitability withAn.stephensipresence. General patterns of poleward expansion for thermal suitability were seen for bothP.falciparumandP.vivaxtransmission potential.

   Understanding the potential suitability forAn.stephensitransmission in a changing climate provides a key tool for planning, given an ongoing invasion and expansion of the vector. Anticipating the potential impact of onward expansion to transmission suitable areas, and the size of population at risk under future climate scenarios, and where they occur, can serve as a large-scale call for attention, planning, and monitoring.

    

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3. Inferring person-to-person networks of Plasmodium falciparum transmission: are analyses of routine surveillance data up to the task?

   https://doi.org/10.1186/s12936-022-04072-2  

   Huber, John H. ; Hsiang, Michelle S. ; Dlamini, Nomcebo ; Murphy, Maxwell ; Vilakati, Sibonakaliso ; Nhlabathi, Nomcebo ; Lerch, Anita ; Nielsen, Rasmus ; Ntshalintshali, Nyasatu ; Greenhouse, Bryan ; et al ( February 2022 , Malaria Journal)

   Inference of person-to-person transmission networks using surveillance data is increasingly used to estimate spatiotemporal patterns of pathogen transmission. Several data types can be used to inform transmission network inferences, yet the sensitivity of those inferences to different data types is not routinely evaluated.

   The influence of different combinations of spatial, temporal, and travel-history data on transmission network inferences forPlasmodium falciparummalaria were evaluated.

   The information content of these data types may be limited for inferring person-to-person transmission networks and may lead to an overestimate of transmission. Only when outbreaks were temporally focal or travel histories were accurate was the algorithm able to accurately estimate the reproduction number under control,R_c. Applying this approach to data from Eswatini indicated that inferences ofR_cand spatiotemporal patterns therein depend upon the choice of data types and assumptions about travel-history data.

   These results suggest that transmission network inferences made with routine malaria surveillance data should be interpreted with caution.

    

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4. Ancient Plasmodium genomes shed light on the history of human malaria

   https://doi.org/10.1038/s41586-024-07546-2  

   Michel, Megan ; Skourtanioti, Eirini ; Pierini, Federica ; Guevara, Evelyn K ; Mötsch, Angela ; Kocher, Arthur ; Barquera, Rodrigo ; Bianco, Raffaela A ; Carlhoff, Selina ; Coppola_Bove, Lorenza ; et al ( July 2024 , Nature)

   Malaria-causing protozoa of the genusPlasmodiumhave exerted one of the strongest selective pressures on the human genome, and resistance alleles provide biomolecular footprints that outline the historical reach of these species¹. Nevertheless, debate persists over when and how malaria parasites emerged as human pathogens and spread around the globe^1,2. To address these questions, we generated high-coverage ancient mitochondrial and nuclear genome-wide data fromP. falciparum,P. vivaxandP. malariaefrom 16 countries spanning around 5,500 years of human history. We identifiedP. vivaxandP. falciparumacross geographically disparate regions of Eurasia from as early as the fourth and first millenniabce, respectively; forP. vivax, this evidence pre-dates textual references by several millennia³. Genomic analysis supports distinct disease histories forP. falciparumandP. vivaxin the Americas: similarities between now-eliminated European and peri-contact South American strains indicate that European colonizers were the source of AmericanP. vivax, whereas the trans-Atlantic slave trade probably introducedP. falciparuminto the Americas. Our data underscore the role of cross-cultural contacts in the dissemination of malaria, laying the biomolecular foundation for future palaeo-epidemiological research into the impact ofPlasmodiumparasites on human history. Finally, our unexpected discovery ofP. falciparumin the high-altitude Himalayas provides a rare case study in which individual mobility can be inferred from infection status, adding to our knowledge of cross-cultural connectivity in the region nearly three millennia ago.

    

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5. Temperature impacts the environmental suitability for malaria transmission by Anopheles gambiae and Anopheles stephensi

   https://doi.org/10.1002/ecy.3685  

   Villena, Oswaldo C. ; Ryan, Sadie J. ; Murdock, Courtney C. ; Johnson, Leah R. ( June 2022 , Ecology)

   Extrinsic environmental factors influence the spatiotemporal dynamics of many organisms, including insects that transmit the pathogens responsible for vector‐borne diseases (VBDs). Temperature is an especially important constraint on the fitness of a wide variety of ectothermic insects. A mechanistic understanding of how temperature impacts traits of ectotherms, and thus the distribution of ectotherms and vector‐borne infections, is key to predicting the consequences of climate change on transmission of VBDs like malaria. However, the response of transmission to temperature and other drivers is complex, as thermal traits of ectotherms are typically nonlinear, 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 falciparumandPlasmodium vivax, by two malaria vector species,Anopheles gambiaeandAnopheles stephensi. We model the nonlinear responses of temperature dependent mosquito and parasite traits (mosquito development rate, bite rate, fecundity, proportion of eggs surviving to adulthood, 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, but may differ at the thermal limits. More specifically, we found significant differences in the upper thermal limit between parasites spread by the same mosquito (A. stephensi) and between mosquitoes carryingP. 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.,A. stephensiandA. gambiaeboth withP. falciparum). Using prevalence data, we show that the transmission suitability metric calculated from our mechanistic model is consistent with observedP. falciparumprevalence in Africa and Asia but is equivocal forP. vivaxprevalence in Asia, and inconsistent withP. vivaxprevalence in Africa. We mapped risk to illustrate the number of months various areas in Africa and Asia predicted to be suitable for malaria transmission based on this suitability metric. This mapping provides spatially explicit predictions for suitability and transmission risk.

    

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