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1. Why the growth of arboviral diseases necessitates a new generation of global risk maps and future projections

   https://doi.org/10.1371/journal.pcbi.1012771  

   Brady, Oliver J; Bastos, Leonardo S; Caldwell, Jamie M; Cauchemez, Simon; Clapham, Hannah E; Dorigatti, Illaria; Gaythorpe, Katy_A M; Hu, Wenbiao; Hussain-Alkhateeb, Laith; Johansson, Michael A; et al (April 2025, PLOS Computational Biology)

   Alizon, Samuel (Ed.)

   Global risk maps are an important tool for assessing the global threat of mosquito and tick-transmitted arboviral diseases. Public health officials increasingly rely on risk maps to understand the drivers of transmission, forecast spread, identify gaps in surveillance, estimate disease burden, and target and evaluate the impact of interventions. Here, we describe how current approaches to mapping arboviral diseases have become unnecessarily siloed, ignoring the strengths and weaknesses of different data types and methods. This places limits on data and model output comparability, uncertainty estimation and generalisation that limit the answers they can provide to some of the most pressing questions in arbovirus control. We argue for a new generation of risk mapping models that jointly infer risk from multiple data types. We outline how this can be achieved conceptually and show how this new framework creates opportunities to better integrate epidemiological understanding and uncertainty quantification. We advocate for more co-development of risk maps among modellers and end-users to better enable risk maps to inform public health decisions. Prospective validation of risk maps for specific applications can inform further targeted data collection and subsequent model refinement in an iterative manner. If the expanding use of arbovirus risk maps for control is to continue, methods must develop and adapt to changing questions, interventions and data availability. 

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2. Exploring the Mosquito–Arbovirus Network: A Survey of Vector Competence Experiments

   https://doi.org/10.4269/ajtmh.22-0511  

   Chen, Binqi; Sweeny, Amy R.; Wu, Velen Y.; Christofferson, Rebecca C.; Ebel, Gregory; Fagre, Anna C.; Gallichotte, Emily; Kading, Rebekah C.; Ryan, Sadie J.; Carlson, Colin J. (May 2023, The American Journal of Tropical Medicine and Hygiene)

   ABSTRACT. Arboviruses receive heightened research attention during major outbreaks or when they cause unusual or severe clinical disease, but they are otherwise undercharacterized. 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 more than 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. 

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3. The overlapping global distribution of dengue, chikungunya, Zika and yellow fever

   https://doi.org/10.1038/s41467-025-58609-5  

   Lim, Ahyoung; Shearer, Freya M; Sewalk, Kara; Pigott, David M; Clarke, Joseph; Ghouse, Azhar; Judge, Ciara; Kang, Hyolim; Messina, Jane P; Kraemer, Moritz_U G; et al (December 2025, Nature Communications)

   Abstract Arboviruses transmitted mainly byAedes(Stegomyia)aegyptiandAe. albopictus, including dengue, chikungunya, and Zika viruses, and yellow fever virus in urban settings, pose an escalating global threat. Existing risk maps, often hampered by surveillance biases, may underestimate or misrepresent the true distribution of these diseases and do not incorporate epidemiological similarities despite shared vector species. We address this by generating new global environmental suitability maps forAedes-borne arboviruses using a multi-disease ecological niche model with a nested surveillance model fit to a dataset of over 21,000 occurrence points. This reveals a convergence in suitability around a common global distribution with recent spread of chikungunya and Zika closely aligning with areas suitable for dengue. We estimate that 5.66 (95% confidence interval 5.64-5.68) billion people live in areas suitable for dengue, chikungunya and Zika and 1.54 (1.53-1.54) billion people for yellow fever. We find large national and subnational differences in surveillance capabilities with higher income more accessible areas more likely to detect, diagnose and report viral diseases, which may have led to overestimation of risk in the United States and Europe. When combined with estimates of uncertainty, these suitability maps can be used by ministries of health to target limited surveillance and intervention resources in new strategies against these emerging threats. 

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4. Not all mosquitoes are created equal: A synthesis of vector competence experiments reinforces virus associations of Australian mosquitoes

   https://doi.org/10.1371/journal.pntd.0010768  

   Kain, Morgan P.; Skinner, Eloise B.; Athni, Tejas S.; Ramirez, Ana L.; Mordecai, Erin A.; van den Hurk, Andrew F. (October 2022, PLOS Neglected Tropical Diseases)

   Brackney, Doug E. (Ed.)

   The globalization of mosquito-borne arboviral diseases has placed more than half of the human population at risk. Understanding arbovirus ecology, including the role individual mosquito species play in virus transmission cycles, is critical for limiting disease. Canonical virus-vector groupings, such as Aedes - or Culex -associated flaviviruses, have historically been defined using virus detection in field-collected mosquitoes, mosquito feeding patterns, and vector competence, which quantifies the intrinsic ability of a mosquito to become infected with and transmit a virus during a subsequent blood feed. Herein, we quantitatively synthesize data from 68 laboratory-based vector competence studies of 111 mosquito-virus pairings of Australian mosquito species and viruses of public health concern to further substantiate existing canonical vector-virus groupings and quantify variation within these groupings. Our synthesis reinforces current canonical vector-virus groupings but reveals substantial variation within them. While Aedes species were generally the most competent vectors of canonical “ Aedes -associated flaviviruses” (such as dengue, Zika, and yellow fever viruses), there are some notable exceptions; for example, Aedes notoscriptus is an incompetent vector of dengue viruses. Culex spp. were the most competent vectors of many traditionally Culex -associated flaviviruses including West Nile, Japanese encephalitis and Murray Valley encephalitis viruses, although some Aedes spp. are also moderately competent vectors of these viruses. Conversely, many different mosquito genera were associated with the transmission of the arthritogenic alphaviruses, Ross River, Barmah Forest, and chikungunya viruses. We also confirm that vector competence is impacted by multiple barriers to infection and transmission within the mesenteron and salivary glands of the mosquito. Although these barriers represent important bottlenecks, species that were susceptible to infection with a virus were often likely to transmit it. Importantly, this synthesis provides essential information on what species need to be targeted in mosquito control programs. 

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5. Neglected tropical diseases risk correlates with poverty and early ecosystem destruction

   https://doi.org/10.1186/s40249-023-01084-1  

   Magalhães, Arthur Ramalho; Codeço, Cláudia Torres; Svenning, Jens-Christian; Escobar, Luis E.; Van de Vuurst, Paige; Gonçalves-Souza, Thiago (December 2023, Infectious Diseases of Poverty)

   Abstract BackgroundNeglected tropical diseases affect the most vulnerable populations and cause chronic and debilitating disorders. Socioeconomic vulnerability is a well-known and important determinant of neglected tropical diseases. For example, poverty and sanitation could influence parasite transmission. Nevertheless, the quantitative impact of socioeconomic conditions on disease transmission risk remains poorly explored. MethodsThis study investigated the role of socioeconomic variables in the predictive capacity of risk models of neglected tropical zoonoses using a decade of epidemiological data (2007–2018) from Brazil. Vector-borne diseases investigated in this study included dengue, malaria, Chagas disease, leishmaniasis, and Brazilian spotted fever, while directly-transmitted zoonotic diseases included schistosomiasis, leptospirosis, and hantaviruses. Environmental and socioeconomic predictors were combined with infectious disease data to build environmental and socioenvironmental sets of ecological niche models and their performances were compared. ResultsSocioeconomic variables were found to be as important as environmental variables in influencing the estimated likelihood of disease transmission across large spatial scales. The combination of socioeconomic and environmental variables improved overall model accuracy (or predictive power) by 10% on average (P < 0.01), reaching a maximum of 18% in the case of dengue fever. Gross domestic product was the most important socioeconomic variable (37% relative variable importance, all individual models exhibitedP < 0.00), showing a decreasing relationship with disease indicating poverty as a major factor for disease transmission. Loss of natural vegetation cover between 2008 and 2018 was the most important environmental variable (42% relative variable importance,P < 0.05) among environmental models, exhibiting a decreasing relationship with disease probability, showing that these diseases are especially prevalent in areas where natural ecosystem destruction is on its initial stages and lower when ecosystem destruction is on more advanced stages. ConclusionsDestruction of natural ecosystems coupled with low income explain macro-scale neglected tropical and zoonotic disease probability in Brazil. Addition of socioeconomic variables improves transmission risk forecasts on tandem with environmental variables. Our results highlight that to efficiently address neglected tropical diseases, public health strategies must target both reduction of poverty and cessation of destruction of natural forests and savannas. 

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