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This study employs landscape genetics to investigate the environmental drivers of a deadly vector-borne disease, malaria caused by Plasmodium falciparum, in a more spatially comprehensive manner than any previous work. With 1804 samples from 44 sites collected in western Kenya in 2012 and 2013, we performed resistance surface analysis to show that Lake Victoria acts as a barrier to transmission between areas north and south of the Winam Gulf. In addition, Mantel correlograms clearly showed significant correlations between genetic and geographic distance over short distances (less than 70 km). In both cases, we used an identity-by-state measure of relatedness tailored to find highly related individual parasites in order to focus on recent gene flow that is more relevant to disease transmission. To supplement these results, we performed conventional population genetics analyses, including Bayesian clustering methods and spatial ordination techniques. These analyses revealed some differentiation on the basis of geography and elevation and a cluster of genetic similarity in the lowlands north of the Winam Gulf of Lake Victoria. Taken as a whole, these results indicate low overall genetic differentiation in the Lake Victoria region, but with some separation of parasite populations north and south of the Winam Gulf that is explained by the presence of the lake as a geographic barrier to gene flow. We recommend similar landscape genetics analyses in future molecular epidemiology studies of vector-borne diseases to extend and contextualize the results of traditional population genetics.

Abstract Background Emodepside is an anthelmintic used in veterinary medicine that is currently under investigation in human clinical trials for the treatment of soil-transmitted helminths and possibly Onchocerca volvulus. Emodepside targets the calcium-activated voltage-gated potassium slowpoke 1 (SLO-1) channels of presynaptic nerves of pharynx and body wall muscle cells of nematodes leading to paralysis, reduced locomotion and egg laying, starvation, and death. Emodepside also has activity against Drosophila melanogaster SLO-1 channels. Orthologous SLO-1 genes are present in Anopheles gambiae and Aedes aegypti, suggesting that emodepside may have activity against mosquitoes. Methods Both Anopheles dirus and Ae. aegypti were blood-fed emodepside across a range of concentrations (1–10,000 nM) and mosquito survival was monitored for 10 days. Co-feeding experiments were also performed with An. dirus blood fed ivermectin at the concentrations that kills 25% (LC25) and 50% (LC50) of mosquitoes with and without emodepside at clinical peak concentration in humans (Cmax) and five times the Cmax, and mosquito survival was monitored for 10 days. Results Emodepside had weak mosquito-lethal effects in An. dirus but none observed in Ae. aegypti at the concentrations evaluated. The An. dirus emodepside LC50 was 4,623 [4,159–5,066] ng/ml which is > 100-fold greater than the peak concentrations seen in human. The ivermectin and emodepside co-feed experiment with An. dirus did not indicate any altered effect of ivermectin on mosquito survival when emodepside co-fed at human Cmax or five times that of the human Cmax. Conclusions Emodepside was not lethal to An. dirus at human-relevant concentrations and had no effect on Ae. aegypti survival. Thus, mass distribution of emodepside does not appear to be a potential tool for vector-borne disease control. Emodepside induced mortality in An. dirus does suggest that the SLO-1 channel could be a potential target for novel vector control and may warrant further investigation.

Based on the diversity of transmission routes and host heterogeneity of some infectious diseases, a dynamical model with multi-age-structured, asymptomatic infections, as well as horizontal and vectorial transmission, is proposed. First, the existence and uniqueness of the global positive solution of this model is discussed and the exact expression of the basic reproduction number $ \mathcal{R}_0 $ is obtained using the linear approximation method. Further, we deduce that the disease-free steady state $ \mathcal{E}^0 $ is globally asymptotically stable for $ \mathcal{R}_0 < 1 $, the endemic steady state $ \mathcal{E}^* $ exists and the disease is persistent for $ \mathcal{R}_0 > 1 $. In addition, the locally asymptotically stability of $ \mathcal{E}^* $ is also obtained under some certain conditions. Next, our model is extended to a control problem and the existence and uniqueness of the optimal control by using the Gateaux derivative. Finally, numerical simulations are used to explain the main theoretical results and discuss the impact of age-structured parameters and control strategies on the prevention and control of vector-borne infectious diseases.

This study proposed and analyzed a vector-borne reaction–diffusion–advection model with vector-bias mechanism and heterogeneous parameters in one-dimensional habitat. The basic reproduction number R0{{\mathfrak{R}}}_{0} in connection with principal eigenvalue of elliptic eigenvalue problem is characterized as the role of determining the threshold dynamics of the system. The main objective of this study is to investigate the asymptotic profiles and monotonicity of R0{{\mathfrak{R}}}_{0} with respect to diffusion rates and advection rates under certain conditions. Through exploring the level set of R0{{\mathfrak{R}}}_{0}, we also find that there exists a unique surface separating the dynamics. Our results also reveal that the infected hosts and vectors will aggregate at the downstream end if the ratio of advection rates and diffusion rates is sufficiently large.

Introduction Chikungunya is a mosquito-borne arboviral disease posing an emerging global public health threat. Understanding the global burden of chikungunya is critical for designing effective prevention and control strategies. However, current estimates of the economic and health impact of chikungunya remain limited and are potentially underestimated. This study aims to provide a comprehensive overview of the chikungunya burden worldwide.Methods We analysed the global burden of chikungunya between 2011 and 2020 and calculated disability-adjusted life years (DALYs) and direct and indirect costs using a data-driven simulation model. The main outcomes were the number of cases, the total DALY burden, and the direct and indirect costs of acute and chronic chikungunya between 2011 and 2020.Results Our study revealed a total of 18.7 million chikungunya cases in 110 countries between 2011 and 2020, causing 1.95 million DALYs. Most of this burden was found in the Latin American and Caribbean region. The total economic burden caused by chikungunya over these 10 years was estimated at $2.8 billion in direct costs and $47.1 billion in indirect costs worldwide. Long-term chronic illness was the source of most costs and DALYs.Conclusion Chikungunya has a higher disease burden than was previously estimated and costs related to the disease are substantial. Especially in combination with its unpredictable nature, chikungunya could significantly impact local health systems. Insights from this study could inform decision makers on the impact of chikungunya on population health and help them to appropriately allocate resources to protect vulnerable populations from this debilitating disease.

Vector-borne diseases pose a significant threat to human health, particularly in regions vulnerable to climate change. Among these diseases, malaria, caused by the parasite Plasmodium falciparum and transmitted through the Anopheles mosquito, remains a major global health concern, particularly in sub-Saharan Africa. This study explores the use of machine learning techniques to identify and predict the impact of climate change on the transmission dynamics of P. falciparum malaria in Africa.The research utilizes a combination of climate data, epidemiological records, and machine learning algorithms to analyze historical patterns and project future trends in malaria transmission. Key climate variables such as temperature, precipitation, humidity, and vegetation cover are integrated into predictive models to assess their influence on the abundance and distribution of mosquito vectors and the parasite's lifecycle. Through the application of machine learning models such as Maximum Entropy, this study aims to uncover complex relationships between climatic factors and malaria transmission dynamics. By training these models on historical data, they can accurately predict future scenarios under various climate change scenarios. The findings of this research will provide valuable insights into the potential impact of climate change on the spatial and temporal distribution of P. falciparum malaria in Africa. Such insights are crucial for designing targeted interventions and adaptation strategies to mitigate the anticipated rise in malaria cases and associated morbidity and mortality in the region. Moreover, the methodology developed in this study can serve as a framework for assessing and addressing the impact of climate change on other vector-borne diseases globally.

Vector-borne diseases (VBDs) are embedded within complex socio-ecological systems. While research has traditionally focused on the direct effects of VBDs on human morbidity and mortality, it is increasingly clear that their impacts are much more pervasive. VBDs are dynamically linked to feedbacks between environmental conditions, vector ecology, disease burden, and societal responses that drive transmission. As a result, VBDs have had profound influence on human history. Mechanisms include: (1) killing or debilitating large numbers of people, with demographic and population-level impacts; (2) differentially affecting populations based on prior history of disease exposure, immunity, and resistance; (3) being weaponised to promote or justify hierarchies of power, colonialism, racism, classism and sexism; (4) catalysing changes in ideas, institutions, infrastructure, technologies and social practices in efforts to control disease outbreaks; and (5) changing human relationships with the land and environment. We use historical and archaeological evidence interpreted through an ecological lens to illustrate how VBDs have shaped society and culture, focusing on case studies from four pertinent VBDs: plague, malaria, yellow fever and trypanosomiasis. By comparing across diseases, time periods and geographies, we highlight the enormous scope and variety of mechanisms by which VBDs have influenced human history.

Many regions in developing countries are transitioning to an industrial economic model, accompanied by rapid population growth, which from one side is a welfare driver (WLF) and on the other side is a demographic pressure, especially a health problem such as vector-borne disease. The problem climaxes when this transition is always accompanied by environmental degradation (ENV), which begins with deforestation. Objective: [1] Determine the direct influence of: [1a] Demographic on DHF incidence, [1b] Demographic on Welfare improvement, [1c] Welfare on DHF incidence, [1d] Environment improvement on DHF incidence, [1e] Environment improvement on performance Welfare; and [2] The indirect influence of Welfare in mediating [2a] Demographic pressure and [2b] Environment improvement on DHF incidence. Research Method: Lampung Province was used as the research locus. Forest Resources Inventory Laboratory of Lampung University as a place for analysis. Postulate SEM (Structural Equation Model) was employed at a 95% confidence level. The endogenous variable was vector-borne disease (reflected by DHF incidence). The two exogenous variables were DMG (reflected by population density and the proportion of age of productive, industrial, and service workers) and ENV (reflected by maximum & minimum air temperature, forested areas, and other land uses). The mediating variable is WLF (reflected by poverty and HDI). Findings: [1] Directly, with a significant effect: [1a] DMG pressure increases DHF (P=0.000) and [1.b] WLF (P=0.000); [1.c] Environment improvement increases welfare (P=0.000) while [1d] reduces DHF; and [1.e] WLF improvement can reduce DHF (P=0.010) and [2] The role of WLF improvement [2a] can significantly reduce the incidence of DHF due to demographic pressure (P=0.007) while also [2b] amplifying environmental improvement in reducing DHF significantly (P=0.023). Novelty:To reduce DHF incidence, Welfare improvement can reverse the negative effects of Demographic pressure as well as act as an amplifier for the role of environmental improvement. Doi: 10.28991/HEF-2024-05-01-03 Full Text: PDF

Climate literacy assesses general understanding of climate, climate change, and its effects on the environment as well as human health. Despite vast scientific evidence to support climate change and its associated consequences, particularly with regards to vector-borne diseases, climate change knowledge, attitudes, and behaviors among the general population is relatively poor. In this study, we conducted a thorough review of the current literature to evaluate the scope of global climate and health literacy studies and identify key areas for improvement. We found that very few climate and health literacy studies were based in low- and middle-income countries, and those that were did not make mention of significant regional climate change impacts and specifically those that increase mosquito-borne disease transmission in high-risk areas. We also noted that of the twenty-three studies included in our final review, most focused their assessments on general climate and climate change knowledge, and not on literacy of the relationships between climate change and environmental impacts or subsequent health outcomes. Our findings make it clear that moving forward, there is a major need for climate and health literacy research to expand upon existing climate literature to include additional assessments of the relationships between certain climate change impacts and infectious diseases in particular, as well as to make available a more comprehensive overview of climate and health information to the public in the future.

IntroductionVector-borne diseases are a public health problem in tropical countries, especially Malaria, Leishmaniasis, Chagas, and the arboviral diseases Dengue, Chikungunya, and Zika. Tropical diseases represent a significant challenge to health systems in developing countries.ObjectiveThis study aimed to explore the association between climatic variables and primary vector-borne diseases in Colombia between 2011-2021.MethodsA retrospective analysis of the epidemiological data of Malaria, Leishmania, Chagas, Dengue, Chikungunya, and Zika and the climatic data recorded in 2011-2021 was carried out. The cases were obtained from SIVIGILA of the Colombian Ministry of Health. The climatic data were obtained from WorldClim.ResultsLeishmania, Malaria, and Chagas occur in the departments of Caquetá (located in the Amazon rainforest), Chocó (known for its high rainfall), and Casanare (a region with a high prevalence of Chagas disease). There was no statistical correlation between the number of cases and climatic variables, except for malaria cases in which precipitation had a Pearson correlation value of 0.415. The results predicted an increase of 1.469 malaria cases for every unit increase in precipitation. The cases of dengue, Zika, and chikungunya had similar behavior, with the majority occurring in the departments of Valle del Cauca, Antioquia, Norte de Santander, and Bolívar.ConclusionsExcept for Malaria, the distribution of cases did not directly correlate with temperature and precipitation. Temperature and precipitation did not explain the epidemiological profile of the studied diseases.

We examine how spatial heterogeneity combines with mobility network structure to influence vector-borne disease dynamics. Specifically, we consider a Ross-Macdonald-type disease model on n spatial locations that are coupled by host movement on a strongly connected, weighted, directed graph. We derive a closed form approximation to the domain reproduction number using a Laurent series expansion, and use this approximation to compute sensitivities of the basic reproduction number to model parameters. To illustrate how these results can be used to help inform mitigation strategies, as a case study we apply these results to malaria dynamics in Namibia, using published cell phone data and estimates for local disease transmission. Our analytical results are particularly useful for understanding drivers of transmission when mobility sinks and transmission hot spots do not coincide.

The review summarizes the data of modern domestic and foreign studies on the mechanisms of evolutionary adaptation of the plague pathogen to transmissive spread by arthropods. The data on the molecular basis of the rapid formation of a highly pathogenic bacterium due to the acquisition of new genetic information; structural and functional changes in the genome, causing the disruption of functionality of some genes that prevent survival in the vector are presented. The stage of the complex life cycle of the pathogen associated with the peculiarities of its stay in the vector’s organism and its tactics of evasion from the action of antibacterial substances formed by the flea is considered. The importance of biofilm formation for effective transmission of the pathogen is discussed. A complex cascade of transcriptional regulators of biofilm in Yersinia pestis is considered, which includes activators and repressors of biofilm formation, as well as regulators of synthesis or modification/transport of exopolysaccharide. The hms-dependent mechanism of biofilm formation in Y. pestis is described in detail, as well as the impact on biofilm formation through the regulation of LPS-related genes and its role in the modification and transport of biofilm exopolysaccharide. The data from our own studies on the variability of genes involved in biofilm formation in the main subspecies of the plague pathogen in comparison with non-main subspecies of the plague pathogen, as well as on the ability of strains of different subspecies to form biofilm not only in the proventriculus of the flea, but also on the cuticle of soil nematodes of the Tylenchida and Rhabditida orders and the genus Panagrolaimus are presented. The latter allows us to assume the possible participation of soil and entomoparasitic nematodes in the removal of Y. pestis biofilms from the soil to the above-ground biocoenosis of the natural plague focus.

In the last few decades, we have witnessed the emergence of new vector-borne diseases (VBDs), the globalization of endemic VBDs, and the urbanization of previously rural VBDs. Data harmonization forms the basis of robust decision-support systems designed to protect at-risk communities from VBD threats. Strong interdisciplinary partnerships, protocols, digital infrastructure, and capacity-building initiatives are essential for facilitating the coproduction of robust multisource data sets. This review provides a foundation for researchers and practitioners embarking on data harmonization efforts to ( a ) better understand the links among environmental degradation, climate change, socioeconomic inequalities, and VBD risk; ( b ) conduct risk assessments, health impact attribution, and projection studies; and ( c ) develop robust early warning and response systems. We draw upon best practices in harmonizing data for two well-studied VBDs, dengue and malaria, and provide recommendations for the evolution of research and digital technology to improve data harmonization for VBD risk management.

As of January 2019, a survey of homeless people in Alameda County, CA, documented 8,022 homeless individuals countywide, including 6,312 unsheltered people. Dozens of homeless encampments exist throughout the County, and most lack sanitation facilities (e.g., rodent-proof garbage storage and weekly waste removal; sanitary toilets; and running water for hand washing, showering, or laundry). This situation represents a breakdown of the sanitation interventions that can lead to the outbreak of vector-borne disease (e.g., 2020 outbreaks of flea-borne typhus in southern California). Some characteristics of surveyed encampments make them more or less suitable for Norway rat population establishment and the exhibition of problems associated with rodent ectoparasites. Many urban encampments are in parts of Oakland that have old infrastructure including sewers that support an endemic population of Norway rats and where there may be undetected sewer breaks that allow these rats into these homeless encampments. Anecdotally, before the introduction of unmanaged leftover food sources (garbage), rats would go virtually unnoticed due to their low population, but with a regular supply of food, their populations apparently skyrocketed. Unmanaged rodent populations at homeless encampments are a major public health concern for local public health, particularly considering that ectoparasites such as fleas are potential rodent-borne disease vectors.

In sub-Saharan Africa, temperatures are generally conducive to malaria transmission, and rainfall provides mosquitoes with optimal breeding conditions. The objective of this study is to assess the impact of future climate change on malaria transmission in West Africa using community-based vector-borne disease models, TRIeste (VECTRI). This VECTRI model, based on bias-corrected data from the Phase 6 Coupled Model Intercomparison Project (CMIP6), was used to simulate malaria parameters, such as the entomological inoculation rate (EIR). Due to the lack of data on confirmed malaria cases throughout West Africa, we first validated the forced VECTRI model with CMIP6 data in Senegal. This comparative study between observed malaria data from the National Malaria Control Program in Senegal (Programme National de Lutte contre le Paludisme, PNLP, PNLP) and malaria simulation data with the VECTRI (EIR) model has shown the ability of the biological model to simulate malaria transmission in Senegal. We then used the VECTRI model to reproduce the historical characteristics of malaria in West Africa and quantify the projected changes with two Shared Socio-economic Pathways (SSPs). The method adopted consists of first studying the climate in West Africa for a historical period (1950–2014), then evaluating the performance of VECTRI to simulate malaria over the same period (1950–2014), and finally studying the impact of projected climate change on malaria in a future period (2015–2100) according to the ssp245 ssp585 scenario. The results showed that low-latitude (southern) regions with abundant rainfall are the areas most affected by malaria transmission. Two transmission peaks are observed in June and October, with a period of high transmission extending from May to November. In contrast to regions with high latitudes in the north, semi-arid zones experience a relatively brief transmission period that occurs between August, September, and October, with the peak observed in September. Regarding projections based on the ssp585 scenario, the results indicate that, in general, malaria prevalence will gradually decrease in West Africa in the distant future. But the period of high transmission will tend to expand in the future. In addition, the shift of malaria prevalence from already affected areas to more suitable areas due to climate change is observed. Similar results were also observed with the ssp245 scenario regarding the projection of malaria prevalence. In contrast, the ssp245 scenario predicts an increase in malaria prevalence in the distant future, while the ssp585 scenario predicts a decrease. These findings are valuable for decision makers in developing public health initiatives in West Africa to mitigate the impact of this disease in the region in the context of climate change.