Biology subjects

Ryan, S. J.

Publications and source records attributed to Ryan, S. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Excitatory Dysfunction and Phenotypic Rescue in a Human Neuronal Model of SCN2A-Related Disorders

SCN2A-related disorders result from pathogenic variants in the gene encoding for the voltage-gated sodium channel Nav1.2. Collectively, these disorders result in variable age of onset epilepsy, autism spectrum disorder, and epileptic encephalopathies. While the mechanisms of haploinsufficiency resulting in autism spectrum disorder have been explored in detail, few studies report the impact of pathogenic missense variants in human neurons. In this work, we combined conventional electrophysiology and high-throughput all-optical electrophysiology assays to analyze the SCN2A p.M1879T pathogenic variant associated with early-onset epilepsy and developmental delay. In both platforms, iPSC-derived excitatory neurons expressing the disease variant showed greater firing at higher stimuli compared to the isogenic control neurons (corrected by CRISPR/Cas9), as well as changes to action potential shape (steeper slope and larger amplitude) with evoked firing. We used machine learning techniques on the optical physiology dataset to classify the two genotypes, finding that sodium channel blocking anti-seizure drugs could restore an isogenic phenotype. This work demonstrates proof of sodium channel blocker efficacy in a human neuronal model of SCN2A-related epilepsy and highlights the power of leveraging high-throughput all-optical electrophysiology for testing drug efficacy.

neuroscience↗

bioRxiv2025

Modeling asymmetric Thermal Performance Curves for proportion data

Ectotherms are subject to temperature impacts on a variety of functional traits, such as fecundity and development. Quantifying the shape of the response of traits to temperature involves fitting (usually) non-linear curves to empirically derived data. This study introduces the LINEX Thermal Performance Curve (TPC), a novel non-linear predictor for modeling asymmetric thermal responses in biological traits. Unlike traditional symmetric TPCs, the LINEX function captures a wide range of asymmetric shapes (e.g., left- or right-skewed), making it particularly suitable for traits like survival or fecundity that often exhibit non-normal, bounded distributions. The study implements the LINEX TPC within a Bayesian framework using the bayesTPC R package. We demonstrate the models flexibility and utility through simulations and experimental data from arthropod thermal traits. Results highlight the LINEX TPCs superior fit for asymmetric traits compared to standard quadratic models, as evidenced by improved performance metrics. The approach addresses challenges in estimating uncertainty in bounded data, providing a robust tool for ecological and evolutionary studies that require precise thermal sensitivity modeling.

ecology↗

bioRxiv2025

MIReVTD, a Minimum Information Standard for Reporting Vector Trait Data

Vector-borne diseases pose a persistent and increasing challenge to human, animal, and agricultural systems globally. Mathematical modeling frameworks incorporating vector trait responses are powerful tools to assess risk and predict vector-borne disease impacts. Developing these frameworks and the reliability of their predictions hinge on the availability of experimentally derived vector trait data for model parameterization and inference of the biological mechanisms underpinning transmission. Trait experiments have generated data for many known and potential vector species, but the terminology used across studies is inconsistent, and accompanying publications may share data with insufficient detail for reuse or synthesis. The lack of data standardization can lead to information loss and prohibits analytical comprehensiveness. Here, we present MIReVTD, a Minimum Information standard for Reporting Vector Trait Data. Our reporting checklist balances completeness and labor- intensiveness with the goal of making these important experimental data easier to find and reuse, without onerous effort for scientists generating the data. To illustrate the standard, we provide an example reproducing results from an Aedes aegypti mosquito study.

ecology↗

bioRxiv2024

Ecological and socioeconomic factors associated with globally reported tick-borne viruses

BackgroundPublic health resources are often allocated based on reported disease cases. However, for lesser-known infectious diseases, such as tick-borne viruses, disease risk reporting should account for more than just the biology of the disease and include mediating factors such as socioeconomics which can determine if an infection gets reported. ObjectivesWe aim to identify country-level ecological and socioeconomic factors important to reporting tick-borne viruses and examine whether countries with more economic resources have a higher likelihood of reporting resource intensive incidences. Our study goals are to determine potential country-level interventions that could enhance recognition of and reduce the health burden associated with tick-borne viruses. MethodsWe apply machine learning to the most comprehensive tick-borne virus database, ZOVER, with a curated global trait matrix of 23 environmental and socioeconomic predictors. ResultsWe identified socioeconomic factors driving reported tick-borne viruses captured in the database at a country level. Countries that were more likely to report tick-borne viruses had a lower Gini Index (i.e., countries with less inequalities such as Nordic countries), increased dollars spent on pesticide imports, and had institutions (i.e., IVSA chapter) or individuals with agricultural, forestry, or veterinary knowledge (i.e., % of tertiary grads) present. Additional characteristics included countries with a lower percent of population exposed to conflict also had a higher probability of reporting a tick-borne virus. As expected, broad environmental factors such as the Koeppen-Geiger climate classification zone was important and identified Mediterranean climate or humid subtropical climate as environmentally suitable zones for reported tick-borne viruses. DiscussionFor environmentally persistent pathogens, the role of ancillary factors mediating reporting must be considered for allocating resources to interventions. In addition, while direct interruption of transmission is important, socioeconomic interventions may be the greatest tool to reduce local disease burden.

ecology↗

bioRxiv2024

Mean daily temperatures can predict the thermal limits of malaria transmission better than rate summation

Temperature shapes the distribution, seasonality, and magnitude of mosquito-borne disease outbreaks. Mechanistic models predicting transmission often use mosquito and pathogen thermal responses from constant temperature experiments. However, mosquitoes live in fluctuating environments. Rate summation (nonlinear averaging) is a common approach to infer performance in fluctuating environments, but its accuracy is rarely validated. We measured three mosquito traits that impact transmission (bite rate, survival, fecundity) in a malaria mosquito (Anopheles stephensi) across temperature gradients with three diurnal temperature ranges (0, 9 and 12{degrees}C). We compared thermal suitability models with temperature-trait relationships observed under constant temperatures, fluctuating temperatures, and those predicted by rate summation. We mapped results across An. stephenesis native Asian and invasive African ranges. We found: 1) daily temperature fluctuation significantly altered trait thermal responses; 2) rate summation partially captured decreases in performance near thermal optima, but also incorrectly predicted increases near thermal limits; and 3) while thermal suitability characterized across constant temperatures did not perfectly capture suitability in fluctuating environments, it was more accurate for estimating and mapping thermal limits than predictions from rate summation. Our study provides insight into methods for predicting mosquito-borne disease risk and emphasizes the need to improve understanding of organismal performance under fluctuating conditions.

ecology↗

bioRxiv2024

Discovery of novel compounds and target mechanisms using a high throughput, multiparametric phenotypic screen in a human neuronal model of Tuberous Sclerosis

Tuberous sclerosis complex (TSC) is a rare genetic disorder caused by mutations in the mTOR pathway genes TSC1 or TSC2. TSC can affect multiple organs including the brain, and most patients (75-90%) present with seizures during early childhood and intractable epilepsy throughout life. mTOR inhibitors, part of the current standard of care, lack the optimal characteristics to fully address patient phenotypes. Here, we report on the application of our all-optical electrophysiology platform for phenotypic screening in a human neuronal model of TSC. We used CRISPR/Cas9-isogenic TSC2-/- iPS cell lines to identify disease-associated changes to neuronal morphology, transcript expression and neuronal excitability. We established a robust multiparametric electrophysiological phenotype which we then validated in TSC patient-derived neurons. We used this phenotype to conduct a screen of [~]30,000 small molecule compounds in human iPS cell-derived neurons and identified chemical scaffolds that rescued the functional TSC disease parameters. Confirmed hits may act via different mechanisms than direct mTOR pathway inhibition. This strategy provides molecular starting points for therapeutic development in TSC and a framework for phenotype discovery and drug screening in other neurological disorders.

neuroscience↗

bioRxiv2023

Trends in mosquito species distribution modeling: insights for vector surveillance and disease control

Species distribution modeling (SDM) has become an increasingly common approach to explore questions about ecology, geography, outbreak risk, and global change as they relate to infectious disease vectors. Here, we conducted a systematic review of the scientific literature, screening 563 abstracts and identifying 204 studies that used SDMs to produce distribution estimates for mosquito species. While the number of studies employing SDM methods has increased markedly over the past decade, the overwhelming majority used a single method (MaxEnt) and focused on human infectious disease vectors or their close relatives. The majority of regional models were developed for areas in Africa and Asia, while more localized modeling efforts were most common for North America and Europe. Findings from this study highlight gaps in taxonomic, geographic, and methodological foci of current SDM literature for mosquitoes that can guide future efforts to study the geography of mosquito-borne disease risk.

ecology↗

bioRxiv2023

Newer Surveillance Data Extends our Understanding of the Niche of Rickettsia montanensis (Rickettsiales: Rickettsiaceae) Infection of the American Dog Tick (Acari: Ixodidae) in the United States.

BackgroundUnderstanding the geographic distribution of Rickettsia montanensis infections in Dermacentor variabilis is important for tick-borne disease management in the United States, as both a tick-borne agent of interest and a potential confounder in surveillance of other rickettsial diseases. Two previous studies modeled niche suitability for D. variabilis with and without R. montanensis, from 2002-2012, indicating that the D. variabilis niche overestimates the infected niche. This study updates these, adding data since 2012. MethodsNewer surveillance and testing data were used to update Species Distribution Models (SDMs) of D. variabilis, and R. montanensis infected D. variabilis, in the United States. Using random forest (RF) models, found to perform best in previous work, we updated the SDMs and compared them with prior results. Warrens I niche overlap metric was used to compare between predicted suitability for all ticks and pathogen positive niche models across datasets. ResultsWarrens I indicated <2% change in predicted niche, and there was no change in order of importance of environmental predictors, for D. variabilis or R. montanensis positive niche. The updated D. variabilis niche model overpredicted suitability compared to the updated R. montanensis positive niche in key peripheral parts of the range, but slightly underpredicted through the northern and midwestern parts of the range. This reinforces previous findings of a more constrained pathogen-positive niche than predicted by D. variabilis records alone. ConclusionsThe consistency of predicted niche suitability for D. variabilis in the United States, with the addition of nearly a decade of new data, corroborates this is a species with generalist habitat requirements. Yet a slight shift in updated niche distribution, even of low suitability, included more southern areas, pointing to a need for continued and extended monitoring and surveillance. This further underscores the importance of revisiting vector and vector-borne disease distribution maps.

ecology↗

bioRxiv2022

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

BackgroundAnopheles stephensi is 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 both P. falciparum (PF) and P. vivax (PV) malaria. Perhaps most alarming, the characteristics of An. stephensi, such as container breeding and anthropophily, make it particularly adept at exploiting built environments in areas with no prior history of malaria risk. MethodsIn this paper we created global maps of thermal transmission suitability and people at risk (PAR) for malaria transmission by An. stephensi, 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. ResultsUsing the Global Burden of Disease regions approach, we found that heterogenous regional increases and decreases in risk did not mask the overall pattern of massive increases of PAR for malaria transmission suitability with An. stephensi presence. General patterns of poleward expansion for thermal suitability were seen for both PF and PV transmission potential. ConclusionsUnderstanding the potential suitability for An. stephensi transmission 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.

ecology↗

bioRxiv2022

Viral diversity and zoonotic risk in endangered species

A growing body of evidence links zoonotic disease risk, including pandemic threats, to biodiversity loss and other upstream anthropogenic impacts on ecosystem health. However, there is little current research assessing viral diversity in endangered species. Here, combining IUCN Red List data on 5,876 mammal species with data on host-virus associations for a subset of 1,273 extant species, we examine the relationship between endangered species status and viral diversity, including the subset of viruses that can infect humans (zoonotic viruses). We show that fewer total viruses and fewer zoonotic viruses are known to infect more threatened species. After correcting for sampling effort, zoonotic virus diversity is mostly independent of threat status, but endangered species--despite a higher apparent research effort--have a significantly lower diversity of viruses, a property that is not explained by collinearity with host phylogeography or life history variation. Although this pattern could be generated by real biological processes, we suspect instead that endangered species may be subject to additional sampling biases not captured by the total volume of scientific literature (e.g., lower rates of invasive sampling may decrease viral discovery). Overall, our findings suggest that endangered species are no more or less likely to host viruses that pose a threat to humans, but future zoonotic threats might remain undiscovered in these species. This may be concerning, given that drivers of endangered species vulnerability such as habitat disturbance, wildlife trade, or climate vulnerability may increase virus prevalence in reservoirs and risk of spillover into humans.

ecology↗

bioRxiv2022

Exploring the mosquito-arbovirus network: a survey of vector competence experiments

Arboviruses receive heightened research attention during major outbreaks, or when they cause unusual or severe clinical disease, but are otherwise under-characterized. Global change is also accelerating the emergence and spread of arboviral diseases, leading to time sensitive questions about potential interactions between viruses and novel vectors. Vector competence experiments help determine the susceptibility of certain arthropods to a given arbovirus, but these experiments are often conducted in real-time during outbreaks, rather than with preparedness in mind. We conducted a systematic review of reported mosquito-arbovirus competence experiments, screening 570 abstracts to arrive at 265 studies testing in vivo arboviral competence. We found that over 90% of potential mosquito-virus combinations are untested in experimental settings, and that entire regions and their corresponding vectors and viruses are undersampled. These knowledge gaps stymie outbreak response, and limit attempts to both build and validate predictive models of the vector-virus network.

ecology↗

bioRxiv2021

Mammal virus diversity estimates are unstable due to accelerating discovery effort

Host-virus association data form the backbone of research into eco-evolutionary drivers of viral diversity and host-level zoonotic risk. However, knowledge of the wildlife virome is inherently constrained by historical discovery effort, and there are concerns that the reliability of ecological inference from host-virus data may be undermined by taxonomic and geographical sampling biases. Here, we evaluate whether current estimates of host-level viral diversity in wild mammals are stable enough to be considered biologically meaningful, by analysing a comprehensive dataset of discovery dates of 6,571 unique mammal host-virus associations between 1930 and 2018. We show that virus discovery rates in mammal hosts are still either constant or accelerating, with little evidence of declines towards viral richness asymptotes in even highly-sampled hosts. Consequently, inference of relative viral richness across host species has been unstable over time, particularly in bats, where intensified surveillance since the early 2000s caused a rapid rearrangement of species ranked viral richness. Our results show that comparative inference of host-level virus diversity across mammals is highly sensitive to even short-term changes in sampling effort. We advise caution to avoid overinterpreting patterns in current data, since our findings suggest that an analysis conducted today could feasibly draw quite different conclusions than one conducted only a decade ago.

ecology↗

bioRxiv2021

The Global Virome in One Network (VIRION): an atlas of vertebrate-virus associations

Data cataloguing viral diversity on Earth have been fragmented across sources, disciplines, formats, and various degrees of open collation, posing challenges for research on macroecology, evolution, and public health. Here, we solve this problem by establishing a dynamically-maintained database of vertebrate-virus associations, called The Global Virome in One Network (VIRION). The VIRION database has been assembled through both reconciliation of static datasets and integration of dynamically-updated databases. These data sources are all harmonized against one taxonomic backbone, including metadata on host and virus taxonomic validity and higher classification; additional metadata on sampling methodology and evidence strength are also available in a harmonized format. In total, the VIRION database is the largest open-source, open-access database of its kind, with roughly half a million unique records that include 9,521 resolved virus "species" (of which 1,661 are ICTV ratified), 3,692 resolved vertebrate host species, and 23,147 unique interactions between taxonomically-valid organisms. Together, these data cover roughly a quarter of mammal diversity, a tenth of bird diversity, and ~6% of the estimated total diversity of vertebrates, and a much larger proportion of their virome than any previous database. We show how these data can be used to test hypotheses about microbiology, ecology, and evolution, and make suggestions for best practices that address the unique mix of evidence that coexists in these data.

microbiology↗

bioRxiv2021

Data proliferation, reconciliation, and synthesis in viral ecology

The fields of viral ecology and evolution have rapidly expanded in the last two decades, driven by technological improvements, and motivated by efforts to discover potentially zoonotic wildlife viruses under the rubric of pandemic prevention. One consequence has been a massive proliferation of host-virus association data, which comprise the backbone of research in viral macroecology and zoonotic risk prediction. These data remain fragmented across numerous data portals and projects, each with their own scope, structure, and reporting standards. Here, we propose that synthesis of host-virus association data is a central challenge to improve our understanding of the global virome and develop foundational theory in viral ecology. To illustrate this, we build an open reconciled mammal-virus database from four key published datasets, applying a standardized taxonomy and metadata. We show that reconciling these datasets provides a substantially richer view of the mammal virome than that offered by any one individual database. We argue for a shift in best practice towards the incremental development and use of synthetic datasets in viral ecology research, both to improve comparability and replicability across studies, and to facilitate future efforts to use machine learning to predict the structure and dynamics of the global virome.

ecology↗

bioRxiv2021

Urban-adapted mammal species have more known pathogens

The world is rapidly urbanising, inviting mounting concern that urban environments will experience increased zoonotic disease risk. Urban animals could have more frequent contact with humans, and therefore may transmit more zoonotic parasites; however, these animals have a specific set of underlying traits that may determine their parasite burdens while predisposing them to urban living, and they may be subject to more intense research effort, both of which could complicate our ability to reliably identify the role of urbanisation in driving zoonotic risk. Here, we test whether urban mammal species host more known zoonotic parasites, investigating the potential underlying drivers while accounting for a correlated suite of phenotypic, taxonomic, and geographic predictors. We found that urban-adapted mammals have more documented parasites, and more zoonotic parasites specifically: despite comprising only 157 of the 2792 investigated species (6%), urban mammals provided 39% of known host-parasite combinations and showed consistently higher viral discovery rates throughout the last century. However, contrary to predictions, much of the observed effect was attributable to research effort rather than to urban adaptation status itself, and urban-adapted species in fact hosted fewer zoonoses than expected given their total observed parasite richness. We conclude that extended historical contact with humans has had a limited impact on the number of observed zoonotic parasites in urban-adapted mammals; instead, their greater observed zoonotic richness likely reflects sampling bias arising from proximity to humans, which supports a near-universal underlying pattern of conflation between zoonotic risk, research effort, and synanthropy. These findings underscore the need to resolve the ecological mechanisms underlying links between anthropogenic change, sampling bias, and observed wildlife disease dynamics.

ecology↗

bioRxiv2020

No evidence for insecticide resistance in a homogenous population of Aedes albopictus in Mecklenburg County, North Carolina

Aedes albopictus is a cosmopolitan mosquito species capable of transmitting arboviral diseases such as dengue, chikungunya, and Zika. To control this and similar species, public and private entities often rely on pyrethroid insecticides. Insecticide resistance status and physiological traits, such as body size, may contribute to local patterns of abundance, which is important for planning vector control. In this study, we genetically screened Ae. albopictus collected from June to August, 2017, in Mecklenburg County, North Carolina, for mutations conferring pyrethroid resistance, and examined spatiotemporal patterns of specimen size, as measured by wing length. We hypothesized that size variation would be associated with factors found to influence abundance in similar populations of Ae. albopictus, and could therefore serve as a proxy measure. The genetic screening results indicated that known pyrethroid resistance alleles in two kdr regions are not present in this population. We detected no significant associations between wing length and socioeconomic and landscape factors, but mosquitoes collected in June had significantly longer wing length than in July or August. The lack of resistance indicators suggest that this population has not developed insecticide resistance via voltage-gated sodium channel mutations. The greater wing lengths in June are likely driven by meteorological patterns, suggesting that short-term weather cues may modulate morphological characteristics that, in turn, affect local fecundity and virus transmission potential.

ecology↗

bioRxiv2020

Household and climate factors influence Aedes aegypti risk in the arid city of Huaquillas, Ecuador

Arboviruses transmitted by Aedes aegypti (e.g., dengue, chikungunya, Zika) are of major public health concern on the arid coastal border of Ecuador and Peru. This high transit border is a critical disease surveillance site due to human movement-associated risk of transmission. Local level studies are thus integral to capturing the dynamics and distribution of vector populations and social-ecological drivers of risk, to inform targeted public health interventions. Our study examines factors associated with household-level Ae. aegypti presence in Huaquillas, Ecuador, while accounting for spatial and temporal effects. From January to May of 2017, adult mosquitoes were collected from a cohort of households (n = 63) in clusters (n = 10), across the city of Huaquillas, using aspirator backpacks. Household surveys describing housing conditions, demographics, economics, travel, disease prevention, and city services were conducted by local enumerators. This study was conducted during the normal arbovirus transmission season (January - May), but during an exceptionally dry year. Household level Ae. aegypti presence peaked in February, and counts were highest in weeks with high temperatures and a week after increased rainfall. Presence of Ae. aegypti was highly variable between clusters. Hierarchical generalized linear models were used to explore household social-ecological variables and female Ae. aegypti presence. Houses with Ae. aegypti used larvicide in water tanks and had high awareness of dengue transmission. We found that homes were more likely to have Ae. aegypti when heads of household had lived in the neighborhoods for longer than average (>22 years), when households had more occupants than average (>4.5), had a female head of household, and received more frequent garbage collection. Ae. aegypti presence was less likely in households with reliable water supply and septic systems. Based on our findings, infrastructure access, urban occupancy patterns, and seasonal climate are important considerations for vector control in this city, and even in dry years, this arid environment supports Ae. aegypti breeding habitat. Author summaryMosquito transmitted infectious diseases are a growing concern around the world. The yellow fever mosquito (Aedes aegypti) has been responsible for recent major outbreaks of disease, including dengue fever and Zika. This mosquito prefers to bite humans and lay its eggs in artificial containers such as water tanks and planters. This makes Ae. aegypti well suited to become established in growing urban areas. Controlling these mosquitoes has been an important way to reduce the risk of disease transmission. Studies that are undertaken to understand local factors that contribute to the continued survival of the mosquito can be used to inform control practices. We conducted a study in the largest city on the border of Ecuador and Peru where we collected adult mosquitoes from houses and surveyed household members about their behaviors, perceptions, and housing infrastructure associated with the mosquito vector. Mosquitoes were most numerous in weeks with high temperatures and a week after increased rainfall. Larvicide was a commonly used control strategy in homes where Ae. aegypti was present. We found that houses that had more people, female heads of household, heads of household that had lived in the neighborhood for a long time, and had unreliable water service, were more likely have mosquitoes present, while houses that used septic systems were less likely to have mosquitoes present.

ecology↗

bioRxiv2020

Modeling consensus and distance to delivering indoor residual spray (IRS) implementation strategies to control malaria transmission

BackgroundIndoor residual spraying (IRS) is an effective method to control malaria-transmitting Anopheles mosquitoes and often complements insecticide-treated mosquito nets, the predominant malaria vector control intervention. With insufficient funds to cover every household, malaria control programs must balance the malaria risk to a particular human community against the financial cost of spraying that community. This study creates a framework for modeling the distance to households for targeting IRS implementation, and applies it to potential risk prioritization strategies in four provinces (Luapula, Muchinga, Eastern, and Northern) in Zambia. MethodsWe used optimal network models to assess the travel distance of routes between operations bases and human communities identified through remote sensing. We compared network travel distances to Euclidean distances, to demonstrate the importance of accounting for road route costs. We then compared the distance to reaching communities for different risk prioritization strategies assuming sufficient funds to spray 50% of households, using four underlying malarial risk maps: a) predicted Plasmodium falciparum parasite rate in 2-10 year olds (PfPR), or b) predicted probability of the presence of each of three main malaria transmitting anopheline vectors (An. arabiensis, An. funestus, An. gambiae) ResultsThe estimated one-way network route distance to reach communities to deliver IRS ranged from 0.05 - 115.69 Km. Euclidean distance over and under-estimated these routes by -101.21 - 41.79 Km per trip, as compared to the network route method. There was little overlap between risk map prioritization strategies, both at a district-by-district scale, and across all four provinces. At both scales, agreement for inclusion or exclusion from IRS across all four prioritization strategies occurred in less than 10% of houses. The distances to reaching prioritized communities were either lower, or not statistically different from non-prioritized communities, at both scales of strategy. ConclusionVariation in distance to targeted communities differed depending on risk prioritization strategy used, and higher risk prioritization did not necessarily translate into greater distances in reaching a human community. These findings from Zambia suggest that areas with higher malaria burden may not necessarily be more remote than areas with lower malaria burden.

bioinformatics↗