The role of human movement in the transmission of vector-borne pathogens

Non-household environments make a major contribution to dengue transmission: implications for vector control

The incidence of Aedes-borne pathogens has been increasing despite vector control efforts. Control strategies typically target households (HH), where Aedes mosquitoes breed in HH containers and bite indoors. However, our study in Kenyan cities of Kisumu and Ukunda (2019-2022) revealed high Aedes abundance in public spaces, prompting the question: How important are non-household (NH) environments for dengue transmission and control? Using field data and human activity patterns, we developed an agent-based model simulating transmission across HH and five types of NH environments, which was then used to evaluate preventive (before an epidemic) and reactive (after an epidemic commences) vector control scenarios. Our findings estimate over half of infections occurring in NH settings, particularly workplaces, markets and recreational sites. Container removal was more effective in NH than in HH areas, contrasting with the global focus on HH-based management. Greater reductions in dengue cases occurred with early, high-coverage interventions, especially in NH locations. Additionally, local ecological factors, such as uneven water container distribution, influence control outcomes. This study underscores the importance of vector control in both HH and NH environments in endemic settings. It highlights a specific approach to inform evidence-based decision-making to target limited vector control resources for optimal control.

The impact of climate change on travel-related vector-borne diseases: A case study on dengue virus transmission

INTRODUCTION

Climate change significantly affects global health, particularly through the increased transmission of vector-borne diseases like dengue fever. This study examines how climate change influences the geographical spread of Aedes aegypti mosquitoes, the main carriers of dengue, highlighting its implications for public health worldwide.

MATERIALS AND METHODS

This study employed a comprehensive approach to evaluate the effect of climate change on dengue transmission dynamics. It included environmental data analysis, mosquito population surveys, and dengue case reports. Remote sensing data was used to track changes in temperature, precipitation, and humidity in dengue-prone areas. Field surveys measured mosquito density, while molecular techniques assessed viral load in Aedes mosquitoes. Additionally, mathematical modeling predicted dengue's future spread under various climate scenarios.

RESULTS

The findings indicate a significant correlation between rising temperatures, changing rainfall patterns, and the expansion of Aedes aegypti habitats, resulting in increased mosquito populations in previously non-endemic areas. This ecological shift is linked to a rise in dengue incidence in regions affected by climate change. Projections suggest a 25 % increase in dengue spread by 2050, especially in Southeast Asia, sub-Saharan Africa, and parts of South America.

DISCUSSION

The study highlights the significant effects of climate change on mosquito distribution and the increasing rates of dengue fever. Warmer temperatures and altered rainfall patterns enhance mosquito growth and virus transmission, while global travel aids the spread of the virus. It emphasizes the necessity for early intervention strategies, including better surveillance, vector control, and adaptations to climate changes, to tackle future dengue transmission issues.

Ascertainment of Community Exposure Sites to Ross River Virus During the 2020 Outbreak in Brisbane, Australia

This study investigated potential Ross River virus (RRV) exposure sites in Greater Brisbane during the Queensland coronavirus disease 2019 lockdown (January-July 2020). Using RRV notifications, cluster identification techniques, and mobile phone data for movement network analysis, the study examined 993 RRV cases and 9 million movement trajectories from residential RRV cluster areas (hot spots). The findings revealed that population movement was a key risk factor to RRV incidence within hot spots, whereby highly interconnected areas had more RRV cases during lockdown. While environmental conditions within RRV hot spots were less significant compared with their connectivity, areas with higher vegetation density had fewer RRV cases. The study also noted that individuals from RRV hot spots spent less time in green areas before lockdown than during and after lockdown. The results suggest that population movement significantly influenced the 2020 RRV outbreak. These insights can help adapt current vector control and surveillance protocols to target areas identified in this study.

Characterizing the genetic diversity and population structure of Plasmodium knowlesi in Aceh Province, Indonesia

As in other parts of Southeast Asia, efforts to achieve or sustain malaria elimination in Indonesia have been threatened by the emergence of human infection with the primate species P. knowlesi. To understand the transmission dynamics of this species, investigation of P. knowlesi genetic diversity and population structure is needed. A molecular surveillance study was conducted in two phases between June 2014 and September 2018 at five primary health facilities in Aceh Province, Indonesia, an area nearing malaria elimination. Dried blood spot samples were collected from patients presenting with suspected malaria and testing positive for malaria by microscopy. PCR was performed for molecular confirmation and species identification. Forty-six samples were confirmed to be P. knowlesi, of which 41 were amplified with genotyping targeting ten known P. knowlesi microsatellite markers. For samples within a site, nearly all (9 of 10 loci) or all loci were polymorphic. Across sites, multiple identical haplotypes were observed, though linkage distribution in the population was low (index of association (IAS) = 0.008). The parasite population was indicative of low diversity (expected heterozygosity [HE] =  0.63) and low complexity demonstrated by 92.7% monoclonal infections, a mean multiplicity of infection of 1.06, and a mean within-host infection fixation index (FST) of 0.05. Principal coordinate and neighbour-joining tree analyses indicated that P. knowlesi strains from Aceh were distinct from those reported in Malaysia. In a near-elimination setting in Indonesia, we demonstrate the first evidence that P. knowlesi strains were minimally diverse and were genetically distinct from Malaysian strains, suggesting highly localized transmission and limited connectivity to Malaysia. Ongoing genetic surveillance of P. knowlesi in Indonesia can inform tracking and planning of malaria control and elimination efforts.

Virucidal and Bactericidal Properties of Biocompatible Copper Textiles

The COVID-19 pandemic highlights the global threat posed by emerging viruses, emphasizing the critical need for effective strategies to combat pathogen transmission. Moreover, alongside emerging viruses, the increasing threat of antimicrobial resistance further reinforces the need to develop novel methods for infection control. Anti-pathogenic coatings on textiles offer a promising solution; in this study, three electroless copper-plated fabrics are evaluated for their antipathogenic properties following International Standards Organisation (ISO) standards. Prior to electroless plating, materials are activated either by immersion in a Pd catalyst solution (material A) or by ink-jet printing Cu/Ag catalyst along the weft (material B) or warp thread (material C). This study demonstrates that activation method influences the materials antipathogenic performance, with all materials achieving complete bactericidal/fungicidal neutralization within 30 min of incubation. Material B exhibits up to 4-log virucidal effects within 1 h against viruses such as coronavirus (OC43, 229E), Influenza A (H1N1), and Rotavirus A. Furthermore, biocompatibility testing indicates that material B exhibited low in vitro cytotoxicity. Textile B demonstrates strong antibacterial results even after one year of accelerated aging with no significant difference (P = 0.74) in efficiency against MRSA, highlighting promising applications for infection control in clinical settings reducing pathogen transmission, nosocomial infections and the associated economic burden.

A numbers game: mosquito-based arbovirus surveillance in two distinct geographic regions of Latin America

Aedes mosquitoes, as vectors of medically important arthropod-borne viruses (arboviruses), constitute a major public health threat that requires entomological and epidemiological surveillance to guide vector control programs to prevent and reduce disease transmission. In this study, we present the collaborative effort of 1 year of Aedes ageypti (Linnaeus, 1762) mosquito-based arbovirus surveillance in 2 geographically distinct regions of Latin America (Nicaragua and Ecuador). Adult female mosquitoes were collected using backpack aspirators in over 2,800 randomly selected households (Nicaragua, Ecuador) and 100 key sites (Nicaragua) from 8 distinct communities (Nicaragua: 2, Ecuador: 6). A total of 1,358 mosquito female pools were processed for RNA extraction and viral RNA detection using real-time reverse transcription-polymerase chain reaction. Ten positive dengue virus (DENV) pools were detected (3 in Nicaragua and 7 in Ecuador), all of which were found during the rainy season and matched the serotypes found in humans (Nicaragua: DENV-1 and DENV-4; Ecuador: DENV-2). Infection rates ranged from 1.13 to 23.13, with the Nicaraguan communities having the lowest infection rates. Our results demonstrate the feasibility of detecting DENV-infected Aedes mosquitoes in low-resource settings and underscore the need for targeted mosquito arbovirus sampling and testing, providing valuable insights for future surveillance programs in the Latin American region.

The effects of variable spatial aggregation on lymphatic filariasis transmission

BACKGROUND

Elimination of lymphatic filariasis (LF) is a World Health Organization goal, with several countries at or near prevalence thresholds. Where LF cases remain after mass drug administration, they tend to be spatially clustered, with an overdispersed individual worm burden. Both individual and spatial heterogeneities can cause aggregation of infection; however, few studies have investigated the drivers of heterogeneity and implications for disease elimination.

METHODS

We used a spatially explicit lymphatic filariasis model to investigate LF transmission in American Samoa at three spatial scales - a territory-level model, a village model with 64 groups and a subvillage model with 316 groups.

RESULTS

To reproduce American Samoan survey data, models with less spatial structure required increased individual-level bite aggregation. Threshold behaviour was present in the territory model but less evident in the models with spatial structure. As such, mass drug administration was most effective in the territory model, while in the spatially structured models, successive rounds of mass drug administration only gradually increased the likelihood of elimination. With the addition of spatial structure, residual infections remained in limited groups, and infection resurgence was slowed.

CONCLUSIONS

Due to the impacts on potential intervention and surveillance strategies, it is critical that studies incorporate individual and spatial sources of heterogeneity to accurately model transmission and inform potential policy decisions.

Mobility and non-household environments: understanding dengue transmission patterns in urban contexts

Background

Households (HH) have been traditionally described as the main environments where people are at risk of dengue (and other arbovirus) infection. Mounting entomological evidence has suggested a larger role of environments other than HH in transmission. Recently, an agent-based model (ABM) estimated that over half of infections occur in non-household (NH) environments like workplaces, markets, and recreational sites. However, the importance of human and vector mobility and the configurations of urban spaces in mediating the effects of NH on dengue transmission remains understudied.

Methods

To improve our knowledge of the relevance of NH in transmission, we expanded an ABM calibrated from field data in Kenya to examine movement of people and vectors under different spatial configurations of buildings. In this model, we assessed the number of people traveling between HH and NH and their distance. Those were studied on three different urban configurations, on which the NH are spatially distributed either randomly (scattered), centered (in a single center), or clustered (in more than one cluster).

Results

Across simulations, the number of people moving is a major influential variable where higher levels of movement between HH and NH increases the number of cases. In addition, the number of cases is higher when NH are scattered. Intriguingly, the distance that people travel from HH to NH seems to have little effect on dengue burden; however, it affects the level of spatial clustering of cases.

Conclusions

These results highlight the importance of NH as a major spreader of infections between HH and NH environments supporting the relevance of NH in transmission and its interaction with human movement in driving dengue dynamics.

Epidemiology and global spread of emerging tick-borne Alongshan virus

The emergence and spread of novel viral pathogens is a major threat to human health, particularly in the context of climate and human-induced change in land use. Alongshan virus (ALSV) is a tick-borne virus associated with human disease, which was first identified in northeast China. More recently, several studies reported the emergence of ALSV in mammalian and arthropod hosts in multiple different countries outside of Asia, and the first viral genome sequencing data has become available. ALSV is a member of the Jingmenvirus group closely related to the Flaviviridae family. Unusually, the positive-sense, single-stranded RNA genome of ALSV is segmented and consists of four distinct segments, two of which show homology with the NS3 and NS5 protein encoding regions of non-segmented flaviviruses. Transmission of arthropod-borne pathogens will likely increase in the future due to environmental change mediated by a variety of environmental and ecological factors and increasing human encroachment into wild animal habitats. In this review, we present current knowledge of global ALSV distribution and emergence patterns, highlight genetic diversity, evolution and susceptible species. Finally, we discuss the role of this emerging tick-borne virus in the context of urbanization and global health.

Managing vector-borne diseases in a geoAI-enabled society. Malaria as an example

More than 17 % of all infectious diseases are caused by vector-borne diseases resulting in more than 1 billion cases and over 1 million deaths each year. Of these malaria continues to be a global burden in over eighty countries. As societies become more digitalised, the availability of geospatially enabled health and disease information will become more abundant. With this, the ability to assess health and disease risks in real-time will become a reality. The purpose of this study was to examine how geographic information, geospatial technologies and spatial data science are being used to reduce the burden of vector-borne diseases such as malaria and explore the opportunities that lie ahead with GeoAI and other geospatial technology advancements. Malaria is a dynamic and complex system and as such a range of data and approaches are needed to tackle different parts of the malaria cycle at different local and global scales. Geospatial technologies provide an integrated framework vital for monitoring, analysing and managing vector-borne diseases. GeoAI and technological advancements are useful for enhancing real-time assessments, accelerating the decision making process and spatial targeting of interventions. Training is needed to enhance the use of geospatial information for the management of vector-borne diseases.

Dengue virus importation risks in Africa: a modelling study

BACKGROUND

Dengue is a significant global public health concern that poses a threat in Africa. Particularly, African countries are at risk of viral introductions through air travel connectivity with areas of South America and Asia in which explosive dengue outbreaks frequently occur. Limited reporting and diagnostic capacity hinder a comprehensive assessment of continent-wide transmission dynamics and deployment of surveillance strategies in Africa. In this study, we aimed to identify African airports at high risk of receiving passengers with dengue from Asia, Latin America, and other African countries with high dengue incidence.

METHODS

For this modelling study, air travel flow data were obtained from the International Air Transport Association database for 2019. Data comprised monthly passenger volumes from 14 high-incidence countries outside of Africa and 18 countries within the African continent that reported dengue outbreaks in the past 10 years to 54 African countries, encompassing all 197 commercial airports in both the source and destination regions. The risk of dengue introduction into Africa from countries of high incidence in Asia, Latin America, and within Africa was estimated based on origin-destination air travel flows and epidemic activity at origin. We produced a novel proxy for local dengue epidemic activity using a composite index of theoretical climate-driven transmission suitability and population density, which we used, in addition to travel information in a risk flow model, to estimate importation risk.

FINDINGS

Countries in eastern Africa had a high estimated risk of dengue importation from Asia and other east African countries, whereas for west African countries, the risk of importation was higher from within the region than from countries outside of Africa. Some countries with high risk of importation had low local transmission suitability, which is likely to hamper the risk that dengue importations would lead to local transmission and establishment of a dengue outbreak. Mauritius, Uganda, Côte d'Ivoire, Senegal, and Kenya were identified as countries susceptible to dengue introductions during periods of persistent transmission suitability.

INTERPRETATION

Our study improves data-driven allocation of surveillance resources, in regions of Africa that are at high risk of dengue introduction and establishment, including from regional circulation. Improvements in resource allocation will be crucial in detecting and managing imported cases and could improve local responses to dengue outbreaks.

FUNDING

Rockefeller Foundation, National Institute of Health, EDCTP3 and Horizon Europe Research and Innovation, World Bank Group, Medical Research Foundation, Wellcome Trust, Google, Oxford Martin School Pandemic Genomics programme, and John Fell Fund.

Gaussian Process Emulation for Modeling Dengue Outbreak Dynamics

Epidemiological models that aim for a high degree of biological realism by simulating every individual in a population are unavoidably complex, with many free parameters, which makes systematic explorations of their dynamics computationally challenging. This study investigates the potential of Gaussian Process emulation to overcome this obstacle. To simulate disease dynamics, we developed an individual-based model of dengue transmission that includes factors such as social structure, seasonality, and variation in human movement. We trained three Gaussian Process surrogate models on three outcomes: outbreak probability, maximum incidence, and epidemic duration. These models enable the rapid prediction of outcomes at any point in the eight-dimensional parameter space of the original model. Our analysis revealed that average infectivity and average human mobility are key drivers of these epidemiological metrics, while the seasonal timing of the first infection can influence the course of the epidemic outbreak. We use a dataset comprising more than 1,000 dengue epidemics observed over 12 years in Colombia to calibrate our Gaussian Process model and evaluate its predictive power. The calibrated Gaussian Process model identifies a subset of municipalities with consistently higher average infectivity estimates, highlighting them as promising areas for targeted public health interventions. Overall, this work underscores the potential of Gaussian Process emulation to enable the use of more complex individual-based models in epidemiology, allowing a higher degree of realism and accuracy that should increase our ability to control important diseases such as dengue.

Highway paving dramatically increased dengue transmission in the Amazon

Human mobility drives the spread of many infectious diseases, yet the health impacts of changes in mobility due to new infrastructure development are poorly understood and currently not accounted for in impact assessments. We take a novel quasi-experimental approach to identifying the link between mobility and infectious disease, leveraging historical road upgrades as a proxy for regional human mobility changes. We analyzed how highway paving altered transmission of dengue-a high-burden mosquito-borne disease-via changes in human movement in the Madre de Dios region of Peru. The paving of the Interoceanic Highway through a formerly isolated region of the Amazon in 2009 provided a unique opportunity to quantify the causal impact of road paving on disease transmission. To uncover this relationship, we compared dengue incidence data from healthcare facilities in Madre de Dios near to versus far from the newly paved highway before and after paving, while controlling for observable and unobservable confounding variables (a difference-in-differences causal inference approach). We found that the paving of the highway caused at least an additional 9,826 (95% CI: 8,562-10,684) dengue cases since paving, accounting for 45.2% (95% CI: 39.4%-49.2%) of all dengue cases recorded in the region post highway paving (2009-2022). Our findings demonstrate the impact that infrastructure can have on dengue transmission, likely via its effects on human mobility. As a result, we advocate for future road construction plans in tropical regions to account for potential increases in dengue transmission during impact assessments.

The Impact of Zika Emergence in Remote Communities in Northwestern Ecuador

The Zika virus (ZIKV) epidemic in Latin America (2015-2016) has primarily been studied in urban centers, with less understanding of its impact on smaller rural communities. To address this gap, we analyzed ZIKV seroepidemiology in 6 rural Ecuadorian communities (2018-2019) with varying access to a commercial hub. Seroprevalence ranged from 19% to 54%, measured by nonstructural protein 1 blockade of binding enzyme-linked immunosorbent assay. We observed a decline in ZIKV seroprevalence between 2018 and 2019 that was greater among younger populations, suggesting that the attack rates in the 2015-2016 epidemic were significantly higher than our 2018 observations. These data indicate that the 2015-2016 epidemic included significant transmission in rural and more remote settings. Our observations of high seroprevalence in our area of study highlights the importance of surveillance and research in rural areas lacking robust health systems to manage future Zika outbreaks and vaccine initiatives.

Spatiotemporal Evolution of the Yellow Fever Epidemic in Southeast Brazil from 2016 to 2019

Background: Yellow fever (YF) is a zoonotic disease transmitted by mosquitoes among humans and nonhuman primates. Although urban YF is eradicated, the sylvatic YF has reemerged in some areas of Brazil in the twenty-first century. From 2016 to 2019, a sylvatic YF epidemic occurred in Southeast Brazil, where it had been eradicated in the 1940s. Methods: This study's objective was to describe the epidemic in the states of the Southeast region, based on descriptive, cluster, and mobility analyses. Results: Both the descriptive and cluster analyses showed that the YF cases spread from the state of Minas Gerais southward, causing peaks in cases during the summer months. None of the state capitals was included in the clusters, but the connectivity between the municipalities in Greater Metropolitan São Paulo highlighted potential paths of spread. Despite differences in sociodemographic profiles between the Southeast and North of Brazil (the latter region considered endemic), the epidemiological profile was similar, except for patients' occupation, which was not related to rural work in the Southeast. Conclusion: The results contributed to our understanding of the paths by which YF spread across Southeast Brazil and the epidemiological profile in an area that had gone decades without autochthonous cases.

Assessing Dengue Virus Importation Risks in Africa: A Climate and Travel-Based Model

Background

Dengue is a significant global public health concern that poses a threat to Africa. Particularly, African countries are at risk of viral introductions through air travel connectivity with areas of South America and Asia that experience frequent explosive outbreaks. Limited reporting and diagnostic capacity hinder a comprehensive assessment of continent-wide transmission dynamics and deployment of surveillance strategies in Africa. This study aimed to identify African airports at high risk of receiving dengue infected passengers from Asia, Latin America and other African countries with high dengue incidence.

Methods

The risk of dengue introduction into Africa from countries of high incidence in Africa, Latin America and within Africa was estimated based on origin-destination air travel flows and epidemic activity at origin. We produced a novel proxy for local dengue epidemic activity using a composite index of theoretical climate-driven transmission suitability and population density, which we used, along with travel information in a risk flow model, to estimate importation risk.

Findings

We find that countries in East Africa face higher estimated risk of importation from Asia and other East African countries, whereas for West African countries, larger risk of importation is estimated from within the region. Some countries with high risk of importation experience low local transmission suitability which likely hampers the chances that importations lead to local transmission and establishment. Conversely, Mauritius, Uganda, Ivory Coast, Senegal, and Kenya are identified as countries susceptible to dengue introductions during periods of persistent transmission suitability.

Interpretation

Our work improves data driven allocation of surveillance resources, in regions of Africa that are at high risk of dengue introduction and establishment, including from regional circulation. This will be critical in detecting and managing imported cases and can improve local response to dengue outbreaks.

Funding

Rockefeller Foundation, National Institute of Health, EDCTP3 and Horizon Europe Research and Innovation, World Bank Group, Medical Research Foundation, Wellcome Trust, Google.org, Oxford Martin School Pandemic Genomics programme, John Fell Fund.

Non-household environments make a major contribution to dengue transmission: Implications for vector control

The incidence of Aedes-borne pathogens has been increasing despite vector control efforts. Control strategies typically target households, where Aedes mosquitoes breed in household containers and bite indoors. However, our study in Kenyan cities Kisumu and Ukunda (2019-2022) reveals high Aedes abundance in public spaces, prompting the question: how important are non-household (NH) environments for dengue transmission and control? Using field data and human activity patterns, we developed an agent-based model simulating transmission across household (HH) and five NH environments, which was then used to evaluate preventive (before an epidemic) and reactive (after an epidemic commences) vector control scenarios. Our findings estimate over half of infections occur in NH settings, particularly workplaces, markets, and recreational sites. Control efforts in NH areas proved more effective than HH, contradicting the current global focus. Greater reductions in dengue cases occurred with early, high-coverage interventions, especially in NH locations. Additionally, local ecological factors, such as uneven water container distribution, influence control outcomes. This study underscores the importance of vector control in both household and non-household environments in endemic settings. It highlights a specific approach to inform evidence-based decision making to target limited vector control resources for optimal control.

A mixed method evaluation of knowledge, attitude and practice on dengue fever among Lalitpur Metropolitan City residents: a cross-sectional investigation

BACKGROUND

Dengue poses a significant global public health challenge, including in Nepal. Understanding community's knowledge, attitudes, and behaviors concerning dengue fever is imperative to developing effective prevention and control strategies. This study aimed to assess the knowledge, attitude, and practices related to dengue fever among residents of Lalitpur Metropolitan City.

METHODS

A descriptive cross-sectional household study was conducted using a mixed-method approach, which included quantitatively studying 636 individuals and conducting 20 qualitative interviews. The data was collected between April 2023 and June 2023. The multistage cluster sampling method was applied for household selection during the quantitative study and a purposive judgmental sampling method was used to identify participants for the qualitative interviews. Face-to-face interviews were conducted using a structured questionnaire for the quantitative study and an interview guide for the qualitative study. Quantitative data were analysed using logistic regression in STATA version 13, and thematic analysis was applied to the qualitative data. The findings were validated through triangulation of results from both the qualitative and quantitative study.

RESULTS

Regarding knowledge, 64.94% (n = 413/636) reported being informed about dengue fever. In terms of attitude, a substantial majority, 91.51% (n = 582/636), expressed a positive attitudes toward dengue fever, indicating a favorable perception and knowledge of its significance. Concerning practice, 49.84% (n = 317/636) of respondents reported actively engaging in dengue fever prevention measures. The variables gender, previous history of dengue fever and residency were the determinants of dengue fever knowledge. Additionally, gender, residency, and attitude were predictors of preventive practices concerning dengue fever.

CONCLUSION

Our study revealed that while the community demonstrated good knowledge of dengue fever and positive attitudes toward prevention, their preventive practices were inconsistent, indicating a gap between knowledge and action. A positive attitude was linked to better adherence to preventive measures. To address this gap, it is crucial to promote a positive attitude toward dengue prevention through initiatives like education efforts and social mobilization programs. Implementing Social and Behavior Change Communication (SBCC) programs focused on dengue prevention and control measures can help bridge this knowledge-action gap.

Little disease but lots of bites: social, urbanistic, and entomological risk factors of human exposure to Aedes aegypti in South Texas, U.S

BACKGROUND

Aedes aegypti presence, human-vector contact rates, and Aedes-borne virus transmission are highly variable through time and space. The Lower Rio Grande Valley (LRGV), Texas, is one of the few regions in the U.S. where local transmission of Aedes-borne viruses occurs, presenting an opportunity to evaluate social, urbanistic, entomological, and mobility-based factors that modulate human exposure to Ae. aegypti.

METHODOLOGY & PRINCIPAL FINDINGS

Mosquitoes were collected using BG-Sentinel 2 traps during November 2021 as part of an intervention trial, with knowledge, attitudes, and practices (KAP) and housing quality surveys to gather environmental and demographic data. Human blood samples were taken from individuals and a Bitemark Assay (ELISA) was conducted to quantify human antibodies to the Ae. aegypti Nterm-34kDa salivary peptide as a measure of human exposure to bites. In total, 64 houses were surveyed with 142 blood samples collected. More than 80% of participants had knowledge of mosquito-borne diseases and believed mosquitoes to be a health risk in their community. Our best fit generalized linear mixed effects model found four fixed effects contributed significantly to explaining the variation in exposure to Ae. aegypti bites: higher annual household income, younger age, larger lot area, and higher female Ae. aegypti abundance per trap night averaged over 5 weeks prior to human blood sampling.

CONCLUSIONS

Most surveyed residents recognized mosquitoes and the threat they pose to individual and public health. Urbanistic (i.e., lot size), social (i.e., income within a low-income community and age), and entomological (i.e., adult female Ae. aegypti abundance) factors modulate the risk of human exposure to Ae. aegypti bites. The use of serological biomarker assays, such as the Bitemark Assay, are valuable tools for surveillance and risk assessment of mosquito-borne disease, especially in areas like the LRGV where the transmission of target pathogens is low or intermittent.

Mitigating the Threat of Invasive Mosquito Species Expansion: A Comprehensive Entomological Surveillance Study on Kastellorizo, a Remote Greek Island

The expansion of the tiger mosquito, a vector that can transmit diseases such as dengue, chikungunya, and Zika virus, poses a growing threat to global health. This study focuses on the entomological surveillance of Kastellorizo, a remote Greek island affected by its expansion. This research employs a multifaceted approach, combining KAP survey (knowledge, attitude, practices), mosquito collection using adult traps and human landing catches, and morphological and molecular identification methods. Results from questionnaires reveal community awareness and preparedness gaps, emphasizing the need for targeted education. Mosquito collections confirm the presence of the Aedes albopictus, Aedes cretinus, and Culex pipiens mosquitoes, highlighting the importance of surveillance. This study underscores the significance of community engagement in entomological efforts and proposes a citizen science initiative for sustained monitoring. Overall, this research provides essential insights for developing effective mosquito control programs in remote island settings, thereby emphasizing the importance of adopting a One Health approach to mitigate the spread of vector-borne diseases.

Temperature and time of host-seeking activity impact the efficacy of chemical control interventions targeting the West Nile virus vector, Culex tarsalis

West Nile virus (WNV) is the leading mosquito-borne disease causing-pathogen in the United States. Concerningly, there are no prophylactics or drug treatments for WNV and public health programs rely heavily on vector control efforts to lessen disease incidence. Insecticides can be effective in reducing vector numbers if implemented strategically, but can diminish in efficacy and promote insecticide resistance otherwise. Vector control programs which employ mass-fogging applications of insecticides, often conduct these methods during the late-night hours, when diel temperatures are coldest, and without a-priori knowledge on daily mosquito activity patterns. This study's aims were to 1) quantify the effect of temperature on the toxicity of two conventional insecticides used in fogging applications (malathion and deltamethrin) to Culex tarsalis, an important WNV vector, and 2) quantify the time of host-seeking of Cx. tarsalis and other local mosquito species in Maricopa County, Arizona. The temperature-toxicity relationship of insecticides was assessed using the WHO tube bioassay, and adult Cx. tarsalis, collected as larvae, were exposed to three different insecticide doses at three temperature regimes (15, 25, and 35°C; 80% RH). Time of host-seeking was assessed using collection bottle rotators with encephalitis vector survey traps baited with dry ice, first at 3h intervals during a full day, followed by 1h intervals during the night-time. Malathion became less toxic at cooler temperatures at all doses, while deltamethrin was less toxic at cooler temperatures at the low dose. Regarding time of host-seeking, Cx. tarsalis, Aedes vexans, and Culex quinquefasciatus were the most abundant vectors captured. During the 3-hour interval surveillance over a full day, Cx. tarsalis were most-active during post-midnight biting (00:00-06:00), accounting for 69.0% of all Cx. tarsalis, while pre-midnight biting (18:00-24:00) accounted for 30.0% of Cx. tarsalis. During the 1-hour interval surveillance overnight, Cx. tarsalis were most-active during pre-midnight hours (18:00-24:00), accounting for 50.2% of Cx. tarsalis captures, while post-midnight biting (00:00-06:00) accounted for 49.8% of Cx. tarsalis. Our results suggest that programs employing large-scale applications of insecticidal fogging should consider temperature-toxicity relationships coupled with time of host-seeking data to maximize the efficacy of vector control interventions in reducing mosquito-borne disease burden.

Behaviour and distribution of Aedes aegypti mosquitoes and their relation to dengue incidence in two transmission hotspots in coastal Ecuador

BACKGROUND

Dengue (DENV) transmission is endemic throughout coastal Ecuador, showing heterogeneous incidence patterns in association with fine-scale variation in Aedes aegypti vector populations and other factors. Here, we investigated the impact of micro-climate and neighbourhood-level variation in urbanization on Aedes abundance, resting behaviour and associations with dengue incidence in two endemic areas.

METHODOLOGY/PRINCIPAL FINDINGS

Aedes aegypti were collected in Quinindé and Portoviejo, two urban cantons with hyperendemic dengue transmission in coastal Ecuador. Aedes vectors were sampled in and around houses within urban and peri-urban neighbourhoods at four time periods. We tested for variation in vector abundance and resting behaviour in relation to neighbourhood urbanization level and microclimatic factors. Aedes abundance increased towards the end of the rainy season, was significantly higher in Portoviejo than in Quinindé, and in urban than in peri-urban neighbourhoods. Aedes vectors were more likely to rest inside houses in Portoviejo but had similar abundance in indoor and outdoor resting collections in Quinindé. Over the study period, DENV incidence was lower in Quinindé than in Portoviejo. Relationships between weekly Ae. aegypti abundance and DENV incidence were highly variable between trapping methods; with positive associations being detected only between BG-sentinel and outdoor Prokopack collections.

CONCLUSIONS/SIGNIFICANCE

Aedes aegypti abundance was significantly higher in urban than peri-urban neighbourhoods, and their resting behaviour varied between study sites. This fine-scale spatial heterogeneity in Ae. aegypti abundance and behaviour could generate site-specific variation in human exposure and the effectiveness of indoor-based interventions. The trap-dependent nature of associations between Aedes abundance and local DENV incidence indicates further work is needed to identify robust entomological indicators of infection risk.

A numbers game: Mosquito-based arbovirus surveillance in two distinct geographic regions of Latin America

Aedes mosquitoes, as vectors of medically important arthropod-borne viruses (arboviruses), constitute a major public health threat that requires entomological and epidemiological surveillance to guide vector control programs to prevent and reduce disease transmission. In this study, we present the collaborative effort of one year of mosquito-based arbovirus surveillance in two geographically distinct regions of Latin America (Nicaragua and Ecuador). Adult female mosquitoes were collected using backpack aspirators in over 2,800 randomly selected households (Nicaragua, Ecuador) and 100 key sites (Nicaragua) from eight distinct communities (Nicaragua: 2, Ecuador: 6). A total of 1,358 mosquito female pools were processed for RNA extraction and viral RNA detection using real-time RT-PCR. Ten positive dengue virus (DENV) pools were detected (3 in Nicaragua and 7 in Ecuador), all of which were found during the rainy season and matched the serotypes found in humans (Nicaragua: DENV-1 and DENV-4; Ecuador: DENV-2). Infection rates ranged from 1.13 to 23.13, with the Nicaraguan communities having the lowest infection rates. Our results demonstrate the feasibility of detecting DENV-infected Aedes mosquitoes in low-resource settings and underscore the need for targeted mosquito arbovirus sampling and testing, providing valuable insights for future surveillance programs in the Latin American region.

Comparing malaria risk exposure in rural Cambodia population using GPS tracking and questionnaires

BACKGROUND

The Great Mekong Subregion has attained a major decline in malaria cases and fatalities over the last years, but residual transmission hotspots remain, supposedly fueled by forest workers and migrant populations. This study aimed to: (i) characterize the fine-scale mobility of forest-goers and understand links between their daily movement patterns and malaria transmission, using parasites detection via real time polymerase chain reaction (RT PCR) and the individual exposure to Anopheles bites by quantification of anti-Anopheles saliva antibodies via enzyme-linked immunosorbent assay; (ii) assess the concordance of questionnaires and Global Positioning System (GPS) data loggers for measuring mobility.

METHODS

Two 28 day follow-ups during dry and rainy seasons, including a GPS tracking, questionnaires and health examinations, were performed on male forest goers representing the population at highest risk of infection. Their time spent in different land use categories and demographic data were analyzed in order to understand the risk factors driving malaria in the study area.

RESULTS

Malaria risk varied with village forest cover and at a resolution of only a few kilometers: participants from villages outside the forest had the highest malaria prevalence compared to participants from forest fringe's villages. The time spent in a specific environment did not modulate the risk of malaria, in particular the time spent in forest was not associated with a higher probability to detect malaria among forest-goers. The levels of antibody response to Anopheles salivary peptide among participants were significantly higher during the rainy season, in accordance with Anopheles mosquito density variation, but was not affected by sociodemographic and mobility factors. The agreement between GPS and self-reported data was only 61.9% in reporting each kind of visited environment.

CONCLUSIONS

In a context of residual malaria transmission which was mainly depicted by P. vivax asymptomatic infections, the implementation of questionnaires, GPS data-loggers and quantification of anti-saliva Anopheles antibodies on the high-risk group were not powerful enough to detect malaria risk factors associated with different mobility behaviours or time spent in various environments. The joint implementation of GPS trackers and questionnaires allowed to highlight the limitations of both methodologies and the benefits of using them together. New detection and follow-up strategies are still called for.

The influence of tourist visitation on the heterophyl to lymphocyte ratios and trophic values of Magellanic penguins (Spheniscus magellanicus) at Martillo Island, Argentina

Wildlife tourism is increasing worldwide and monitoring the impact of tourism on wild populations is of the utmost importance for species conservation. The Magellanic penguin Spheniscus magellanicus colony at Martillo Island, Argentina, was studied in the 2016-2020 breeding seasons. In all seasons, adults and chicks belonged to: (i) an area close to or within the tourist trail or (ii) an area far from the tourist trail and out of sight of the tourists. Blood samples were taken for carbon and nitrogen stable isotope composition, in order to estimate trophic niches, and for smears that were made in situ and were then stained in the laboratory where leucocyte counts and differentiation were made under optical microscope. Heterophil to lymphocyte ratios were used as proxies of stress. Repeated sampling showed individual stress levels reduced while wintering. In 2017, stress levels and trophic values were lower than 2018 for the same individuals. Trophic levels did not differ between tourism and no tourism areas within each season, and differed between 2017 and the remaining seasons, indicating a possible diet shift that year. Stress levels were higher for the tourism area than the no tourism area for adults and chicks in all years except for 2020, when stress levels in the tourism area were lower and similar to the no tourism area that year and previous years. Vessel transit within the Beagle Channel and tourist visitation to the penguin colony was greatly reduced in 2020 due to the Covid-19 pandemic. A combination of internal characteristics and external factors may be affecting the stress physiology of individuals. Therefore, future research should include sampling of multiple aspects of penguin physiology, behaviour and environmental context in order to evaluate each effect on Magellanic penguin stress and, ultimately, inform the conservation of this iconic species in time.

A prospective cohort study linking migration, climate, and malaria risk in the Peruvian Amazon

Migration is an important risk factor for malaria transmission for malaria transmission, creating networks that connect Plasmodium between communities. This study aims to understand the timing of why people in the Peruvian Amazon migrated and how characteristics of these migrants are associated with malaria risk. A cohort of 2,202 participants was followed for three years (July 2006 - October 2009), with thrice-weekly active surveillance to record infection and recent travel, which included travel destination(s) and duration away. Migration occurred more frequently in the dry season, but the 7-day rolling mean (7DRM) streamflow was positively correlated with migration events (OR 1.25 (95% CI: 1.138, 1.368)). High-frequency and low-frequency migrant populations reported 9.7 (IRR 7.59 (95% CI:.381, 13.160)) and 4.1 (IRR 2.89 (95% CI: 1.636, 5.099)) times more P. vivax cases than those considered non-migrants and 30.7 (IRR 32.42 (95% CI: 7.977, 131.765)) and 7.4 (IRR 7.44 (95% CI: 1.783, 31.066)) times more P. falciparum cases, respectively. High-frequency migrants employed in manual labour within their community were at 2.45 (95% CI: 1.113, 5.416) times higher risk than non-employed low-frequency migrants. This study confirms the importance of migration for malaria risk as well as factors increasing risk among the migratory community, including, sex, occupation, and educational status.

Assessment of malaria risk in Southeast Asia: a systematic review

BACKGROUND

Several countries in Southeast Asia are nearing malaria elimination, yet eradication remains elusive. This is largely due to the challenge of focusing elimination efforts, an area where risk prediction can play an essential supporting role. Despite its importance, there is no standard numerical method to quantify the risk of malaria infection. Thus, there is a need for a consolidated view of existing definitions of risk and factors considered in assessing risk to analyse the merits of risk prediction models. This systematic review examines studies of the risk of malaria in Southeast Asia with regard to their suitability in addressing the challenges of malaria elimination in low transmission areas.

METHODS

A search of four electronic databases over 2010-2020 retrieved 1297 articles, of which 25 met the inclusion and exclusion criteria. In each study, examined factors included the definition of the risk and indicators of malaria transmission used, the environmental and climatic factors associated with the risk, the statistical models used, the spatial and temporal granularity, and how the relationship between environment, climate, and risk is quantified.

RESULTS

This review found variation in the definition of risk used, as well as the environmental and climatic factors in the reviewed articles. GLM was widely adopted as the analysis technique relating environmental and climatic factors to malaria risk. Most of the studies were carried out in either a cross-sectional design or case-control studies, and most utilized the odds ratio to report the relationship between exposure to risk and malaria prevalence.

CONCLUSIONS

Adopting a standardized definition of malaria risk would help in comparing and sharing results, as would a clear description of the definition and method of collection of the environmental and climatic variables used. Further issues that need to be more fully addressed include detection of asymptomatic cases and considerations of human mobility. Many of the findings of this study are applicable to other low-transmission settings and could serve as a guideline for further studies of malaria in other regions.

Asymptomatic and submicroscopic malaria infections in sugar cane and rice development areas of Ethiopia

BACKGROUND

Water resource development projects, such as dams and irrigation schemes, have a positive impact on food security and poverty reduction. However, such projects could increase prevalence of vector borne disease, such as malaria. This study investigate the impact of different agroecosystems and prevalence of malaria infection in Southwest Ethiopia.

METHODS

Two cross-sectional surveys were conducted in the dry and wet seasons in irrigated and non-irrigated clusters of Arjo sugarcane and Gambella rice development areas of Ethiopia in 2019. A total of 4464 and 2176 study participants from 1449 households in Arjo and 546 households in Gambella enrolled in the study and blood samples were collected, respectively. All blood samples were microscopically examined and a subset of microscopy negative blood samples (n = 2244) were analysed by qPCR. Mixed effect logistic regression and generalized estimating equation were used to determine microscopic and submicroscopic malaria infection and the associated risk factors, respectively.

RESULTS

Prevalence by microscopy was 2.0% (88/4464) in Arjo and 6.1% (133/2176) in Gambella. In Gambella, prevalence was significantly higher in irrigated clusters (10.4% vs 3.6%) than in non-irrigated clusters (p < 0.001), but no difference was found in Arjo (2.0% vs 2.0%; p = 0.993). On the other hand, of the 1713 and 531 samples analysed by qPCR from Arjo and Gambella the presence of submicroscopic infection was 1.2% and 12.8%, respectively. Plasmodium falciparum, Plasmodium vivax, and Plasmodium ovale were identified by qPCR in both sites. Irrigation was a risk factor for submicroscopic infection in both Arjo and Gambella. Irrigation, being a migrant worker, outdoor job, < 6 months length of stay in the area were risk factors for microscopic infection in Gambella. Moreover, school-age children and length of stay in the area for 1-3 years were significant predictors for submicroscopic malaria in Gambella. However, no ITN utilization was a predictor for both submicroscopic and microscopic infection in Arjo. Season was also a risk factor for microscopic infection in Arjo.

CONCLUSION

The study highlighted the potential importance of different irrigation practices impacting on submicroscopic malaria transmission. Moreover, microscopic and submicroscopic infections coupled with population movement may contribute to residual malaria transmission and could hinder malaria control and elimination programmes in the country. Therefore, strengthening malaria surveillance and control by using highly sensitive diagnostic tools to detect low-density parasites, screening migrant workers upon arrival and departure, ensuring adequate coverage and proper utilization of vector control tools, and health education for at-risk groups residing or working in such development corridors is needed.

Effects of human mobility on the spread of Dengue in the region of Caldas, Colombia

According to the World Health Organization (WHO), dengue is the most common acute arthropod-borne viral infection in the world. The spread of dengue and other infectious diseases is closely related to human activity and mobility. In this paper we analyze the effect of introducing mobility restrictions as a public health policy on the total number of dengue cases within a population. To perform the analysis, we use a complex metapopulation in which we implement a compartmental propagation model coupled with the mobility of individuals between the patches. This model is used to investigate the spread of dengue in the municipalities of Caldas (CO). Two scenarios corresponding to different types of mobility restrictions are applied. In the first scenario, the effect of restricting mobility is analyzed in three different ways: a) limiting the access to the endemic node but allowing the movement of its inhabitants, b) restricting the diaspora of the inhabitants of the endemic node but allowing the access of outsiders, and c) a total isolation of the inhabitants of the endemic node. In this scenario, the best simulation results are obtained when specific endemic nodes are isolated during a dengue outbreak, obtaining a reduction of up to 2.5% of dengue cases. Finally, the second scenario simulates a total isolation of the network, i.e., mobility between nodes is completely limited. We have found that this control measure increases the number of total dengue cases in the network by 2.36%.

Methods for measuring short-term geographical mobility used in infectious disease research: a scoping review protocol

INTRODUCTION

Geographical mobility, the movement of individuals or populations, may increase an individual's risk of acquiring or transmitting infectious diseases, including HIV, tuberculosis, malaria and COVID-19. Many studies have collected information on short-term mobility through self-reported travel histories or using GPS trackers, but there has been no consistent conceptualisation and operationalisation of such geographical mobility in global health research. This protocol aims to describe and synthesise different approaches to measuring short-term mobility.

METHODS AND ANALYSIS

We will search three databases (PubMed, Embase and Global Health) for peer-reviewed articles. After removing duplicates, two reviewers will first screen the titles and abstracts and then proceed to full-text screening. We will include studies that measure mobility at the individual level in the context of infectious diseases, including clinical trials, epidemiological studies and analyses of register data. Additional articles for inclusion may be identified through review of references in selected papers. We will summarise the method of data collection (GPS trackers, cellphones, retrospective self-report, travel journal, etc) and the specific measures used (overnight travel, having a secondary residence, travel outside of district, etc).

ETHICS AND DISSEMINATION

This study consists of reviewing and abstracting existing data from publicly available materials, and therefore does not require ethical approval. The results of this study will be submitted for peer reviewed publication and may be presented at a relevant global health conference.

Human movement patterns of farmers and forest workers from the Thailand-Myanmar border

Background: Human travel patterns play an important role in infectious disease epidemiology and ecology. Movement into geographic spaces with high transmission can lead to increased risk of acquiring infections. Pathogens can also be distributed across the landscape via human travel. Most fine scale studies of human travel patterns have been done in urban settings in wealthy nations. Research into human travel patterns in rural areas of low- and middle-income nations are useful for understanding the human components of epidemiological systems for malaria or other diseases of the rural poor. The goal of this research was to assess the feasibility of using GPS loggers to empirically measure human travel patterns in this setting, as well as to quantify differing travel patterns by age, gender, and seasonality among study participants. Methods: In this pilot study we recruited 50 rural villagers from along the Myanmar-Thailand border to carry GPS loggers for the duration of a year. The GPS loggers were programmed to take a time-stamped reading every 30 minutes. We calculated daily movement ranges and multi-day trips by age and gender. We incorporated remote sensing data to assess patterns of days and nights spent in forested or farm areas, also by age and gender. Results: Our study showed that it is feasible to use GPS devices to measure travel patterns, though we had difficulty recruiting women and management of the project was relatively intensive. We found that older adults traveled farther distances than younger adults and adult males spent more nights in farms or forests. Conclusion: The results of this study suggest that further work along these lines would be feasible in this region. Furthermore, the results from this study are useful for individual-based models of disease transmission and land use.

Does ignoring transmission dynamics lead to underestimation of the impact of interventions against mosquito-borne disease?

New vector-control technologies to fight mosquito-borne diseases are urgently needed, the adoption of which depends on efficacy estimates from large-scale cluster-randomised trials (CRTs). The release of Wolbachia-infected mosquitoes is one promising strategy to curb dengue virus (DENV) transmission, and a recent CRT reported impressive reductions in dengue incidence following the release of these mosquitoes. Such trials can be affected by multiple sources of bias, however. We used mathematical models of DENV transmission during a CRT of Wolbachia-infected mosquitoes to explore three such biases: human movement, mosquito movement and coupled transmission dynamics between trial arms. We show that failure to account for each of these biases would lead to underestimated efficacy, and that the majority of this underestimation is due to a heretofore unrecognised bias caused by transmission coupling. Taken together, our findings suggest that Wolbachia-infected mosquitoes could be even more promising than the recent CRT suggested. By emphasising the importance of accounting for transmission coupling between arms, which requires a mathematical model, we highlight the key role that models can play in interpreting and extrapolating the results from trials of vector control interventions.

Humidity - The overlooked variable in the thermal biology of mosquito-borne disease

Vector-borne diseases cause significant financial and human loss, with billions of dollars spent on control. Arthropod vectors experience a complex suite of environmental factors that affect fitness, population growth and species interactions across multiple spatial and temporal scales. Temperature and water availability are two of the most important abiotic variables influencing their distributions and abundances. While extensive research on temperature exists, the influence of humidity on vector and pathogen parameters affecting disease dynamics are less understood. Humidity is often underemphasized, and when considered, is often treated as independent of temperature even though desiccation likely contributes to declines in trait performance at warmer temperatures. This Perspectives explores how humidity shapes the thermal performance of mosquito-borne pathogen transmission. We summarize what is known about its effects and propose a conceptual model for how temperature and humidity interact to shape the range of temperatures across which mosquitoes persist and achieve high transmission potential. We discuss how failing to account for these interactions hinders efforts to forecast transmission dynamics and respond to epidemics of mosquito-borne infections. We outline future research areas that will ground the effects of humidity on the thermal biology of pathogen transmission in a theoretical and empirical framework to improve spatial and temporal prediction of vector-borne pathogen transmission.

Dengue transmission dynamics prediction by combining metapopulation networks and Kalman filter algorithm

Predicting the specific magnitude and the temporal peak of the epidemic of individual local outbreaks is critical for infectious disease control. Previous studies have indicated that significant differences in spatial transmission and epidemic magnitude of dengue were influenced by multiple factors, such as mosquito population density, climatic conditions, and population movement patterns. However, there is a lack of studies that combine the above factors to explain their complex nonlinear relationships in dengue transmission and generate accurate predictions. Therefore, to study the complex spatial diffusion of dengue, this research combined the above factors and developed a network model for spatiotemporal transmission prediction of dengue fever using metapopulation networks based on human mobility. For improving the prediction accuracy of the epidemic model, the ensemble adjusted Kalman filter (EAKF), a data assimilation algorithm, was used to iteratively assimilate the observed case data and adjust the model and parameters. Our study demonstrated that the metapopulation network-EAKF system provided accurate predictions for city-level dengue transmission trajectories in retrospective forecasts of 12 cities in Guangdong province, China. Specifically, the system accurately predicts local dengue outbreak magnitude and the temporal peak of the epidemic up to 10 wk in advance. In addition, the system predicted the peak time, peak intensity, and total number of dengue cases more accurately than isolated city-specific forecasts. The general metapopulation assimilation framework presented in our study provides a methodological foundation for establishing an accurate system with finer temporal and spatial resolution for retrospectively forecasting the magnitude and temporal peak of dengue fever outbreaks. These forecasts based on the proposed method can be interoperated to better support intervention decisions and inform the public of potential risks of disease transmission.

Characterizing dengue transmission in rural areas: A systematic review

Dengue has historically been considered an urban disease associated with dense human populations and the built environment. Recently, studies suggest increasing dengue virus (DENV) transmission in rural populations. It is unclear whether these reports reflect recent spread into rural areas or ongoing transmission that was previously unnoticed, and what mechanisms are driving this rural transmission. We conducted a systematic review to synthesize research on dengue in rural areas and apply this knowledge to summarize aspects of rurality used in current epidemiological studies of DENV transmission given changing and mixed environments. We described how authors defined rurality and how they defined mechanisms for rural dengue transmission. We systematically searched PubMed, Web of Science, and Embase for articles evaluating dengue prevalence or cumulative incidence in rural areas. A total of 106 articles published between 1958 and 2021 met our inclusion criteria. Overall, 56% (n = 22) of the 48 estimates that compared urban and rural settings reported rural dengue incidence as being as high or higher than in urban locations. In some rural areas, the force of infection appears to be increasing over time, as measured by increasing seroprevalence in children and thus likely decreasing age of first infection, suggesting that rural dengue transmission may be a relatively recent phenomenon. Authors characterized rural locations by many different factors, including population density and size, environmental and land use characteristics, and by comparing their context to urban areas. Hypothesized mechanisms for rural dengue transmission included travel, population size, urban infrastructure, vector and environmental factors, among other mechanisms. Strengthening our understanding of the relationship between rurality and dengue will require a more nuanced definition of rurality from the perspective of DENV transmission. Future studies should focus on characterizing details of study locations based on their environmental features, exposure histories, and movement dynamics to identify characteristics that may influence dengue transmission.

The Potential of Surveillance Data for Dengue Risk Mapping: An Evaluation of Different Approaches in Cuba

To better guide dengue prevention and control efforts, the use of routinely collected data to develop risk maps is proposed. For this purpose, dengue experts identified indicators representative of entomological, epidemiological and demographic risks, hereafter called components, by using surveillance data aggregated at the level of Consejos Populares (CPs) in two municipalities of Cuba (Santiago de Cuba and Cienfuegos) in the period of 2010-2015. Two vulnerability models (one with equally weighted components and one with data-derived weights using Principal Component Analysis), and three incidence-based risk models were built to construct risk maps. The correlation between the two vulnerability models was high (tau > 0.89). The single-component and multicomponent incidence-based models were also highly correlated (tau ≥ 0.9). However, the agreement between the vulnerability- and the incidence-based risk maps was below 0.6 in the setting with a prolonged history of dengue transmission. This may suggest that an incidence-based approach does not fully reflect the complexity of vulnerability for future transmission. The small difference between single- and multicomponent incidence maps indicates that in a setting with a narrow availability of data, simpler models can be used. Nevertheless, the generalized linear mixed multicomponent model provides information of covariate-adjusted and spatially smoothed relative risks of disease transmission, which can be important for the prospective evaluation of an intervention strategy. In conclusion, caution is needed when interpreting risk maps, as the results vary depending on the importance given to the components involved in disease transmission. The multicomponent vulnerability mapping needs to be prospectively validated based on an intervention trial targeting high-risk areas.

Inapparent infections shape the transmission heterogeneity of dengue

Transmission heterogeneity, whereby a disproportionate fraction of pathogen transmission events result from a small number of individuals or geographic locations, is an inherent property of many, if not most, infectious disease systems. For vector-borne diseases, transmission heterogeneity is inferred from the distribution of the number of vectors per host, which could lead to significant bias in situations where vector abundance and transmission risk at the household do not correlate, as is the case with dengue virus (DENV). We used data from a contact tracing study to quantify the distribution of DENV acute infections within human activity spaces (AS), the collection of residential locations an individual routinely visits, and quantified measures of virus transmission heterogeneity from two consecutive dengue outbreaks (DENV-4 and DENV-2) that occurred in the city of Iquitos, Peru. Negative-binomial distributions and Pareto fractions showed evidence of strong overdispersion in the number of DENV infections by AS and identified super-spreading units (SSUs): i.e. AS where most infections occurred. Approximately 8% of AS were identified as SSUs, contributing to more than 50% of DENV infections. SSU occurrence was associated more with DENV-2 infection than with DENV-4, a predominance of inapparent infections (74% of all infections), households with high Aedes aegypti mosquito abundance, and high host susceptibility to the circulating DENV serotype. Marked heterogeneity in dengue case distribution, and the role of inapparent infections in defining it, highlight major challenges faced by reactive interventions if those transmission units contributing the most to transmission are not identified, prioritized, and effectively treated.

Relationship between Urban Environmental Components and Dengue Prevalence in Dhaka City-An Approach of Spatial Analysis of Satellite Remote Sensing, Hydro-Climatic, and Census Dengue Data

Dengue fever is a tropical viral disease mostly spread by the Aedes aegypti mosquito across the globe. Each year, millions of people have dengue fever, and many die as a result. Since 2002, the severity of dengue in Bangladesh has increased, and in 2019, it reached its worst level ever. This research used satellite imagery to determine the spatial relationship between urban environmental components (UEC) and dengue incidence in Dhaka in 2019. Land surface temperature (LST), urban heat-island (UHI), land-use-land-cover (LULC), population census, and dengue patient data were evaluated. On the other hand, the temporal association between dengue and 2019 UEC data for Dhaka city, such as precipitation, relative humidity, and temperature, were explored. The calculation indicates that the LST in the research region varies between 21.59 and 33.33 degrees Celsius. Multiple UHIs are present within the city, with LST values ranging from 27 to 32 degrees Celsius. In 2019, these UHIs had a higher incidence of dengue. NDVI values between 0.18 and 1 indicate the presence of vegetation and plants, and the NDWI identifies waterbodies with values between 0 and 1. About 2.51%, 2.66%, 12.81%, and 82% of the city is comprised of water, bare ground, vegetation, and settlement, respectively. The kernel density estimate of dengue data reveals that the majority of dengue cases were concentrated in the city's north edge, south, north-west, and center. The dengue risk map was created by combining all of these spatial outputs (LST, UHI, LULC, population density, and dengue data) and revealed that UHIs of Dhaka are places with high ground temperature and lesser vegetation, waterbodies, and dense urban characteristics, with the highest incidence of dengue. The average yearly temperature in 2019 was 25.26 degrees Celsius. May was the warmest month, with an average monthly temperature of 28.83 degrees Celsius. The monsoon and post-monsoon seasons (middle of March to middle of September) of 2019 sustained higher ambient temperatures (>26 °C), greater relative humidity (>80%), and at least 150 mm of precipitation. The study reveals that dengue transmits faster under climatological circumstances characterized by higher temperatures, relative humidity, and precipitation.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

An insight to better understanding cross border malaria in Saudi Arabia

BACKGROUND

Border malaria is a major obstacle for the malaria elimination in Saudi Arabia. Today, the southern border of Saudi Arabia is a region where malaria cases are resurging, and malaria control is dwindling mainly due to the humanitarian crisis and the conflict in Yemen. This study analyses the current border malaria epidemiology along the southern border of Saudi Arabia from 2015 to 2018.

METHODS

All reported cases maintained by the malaria elimination centres in Aledabi and Baish, Jazan Province, Saudi Arabia, from 2015 to 2018 were analysed to examine the epidemiological changes over time. Pearson's Chi-Square test of differences was utilized to assess differences between the characteristics of imported and local causes and between border cases. A logistic regression model was used to predict imported status was related to living along side of the border area.

RESULTS

A total of 3210 malaria cases were reported in Baish and Aledabi malaria centres between 2015 and 2018, of which 170 were classified as local cases and 3040 were classified as imported cases. Reported malaria cases were mainly among males, within the imported cases 61.5% (1868/3039) were residents of the border areas.

CONCLUSIONS

Given the complexity of cross-border malaria, creating a malaria buffer zone that covers a certain margin from both sides of the border would allow for a joint force, cross-border malaria elimination programme. To initiate a malaria elimination activity and cases reported as belonging to this zone, rather than being pushed from one country to the other, would allow malaria elimination staff to work collaboratively with local borderland residents and other stakeholders to come up with innovative solutions to combat malaria and reach malaria-free borders.

Diseases spectrum in the field of spatiotemporal patterns mining of infectious diseases epidemics: A bibliometric and content analysis

Numerous investigations of the spatiotemporal patterns of infectious disease epidemics, their potential influences, and their driving mechanisms have greatly contributed to effective interventions in the recent years of increasing pandemic situations. However, systematic reviews of the spatiotemporal patterns of communicable diseases are rare. Using bibliometric analysis, combined with content analysis, this study aimed to summarize the number of publications and trends, the spectrum of infectious diseases, major research directions and data-methodological-theoretical characteristics, and academic communities in this field. Based on 851 relevant publications from the Web of Science core database, from January 1991 to September 2021, the study found that the increasing number of publications and the changes in the disease spectrum have been accompanied by serious outbreaks and pandemics over the past 30 years. Owing to the current pandemic of new, infectious diseases (e.g., COVID-19) and the ravages of old infectious diseases (e.g., dengue and influenza), illustrated by the disease spectrum, the number of publications in this field would continue to rise. Three logically rigorous research directions-the detection of spatiotemporal patterns, identification of potential influencing factors, and risk prediction and simulation-support the research paradigm framework in this field. The role of human mobility in the transmission of insect-borne infectious diseases (e.g., dengue) and scale effects must be extensively studied in the future. Developed countries, such as the USA and England, have stronger leadership in the field. Therefore, much more effort must be made by developing countries, such as China, to improve their contribution and role in international academic collaborations.

Risk Factors Associated with the Spatiotemporal Spread of the SARS-CoV-2 Omicron BA.2 Variant — Shanghai Municipality, China, 2022

What is already known about this topic?

Previous studies have explored the spatial transmission patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and have assessed the associated risk factors. However, none of these studies have quantitatively described the spatiotemporal transmission patterns and risk factors for Omicron BA.2 at the micro (within-city) scale.

What is added by this report?

This study highlights the heterogeneous spread of the 2022 Omicron BA.2 epidemic in Shanghai, and identifies associations between different metrics of spatial spread at the subdistrict level and demographic and socioeconomic characteristics of the population, human mobility patterns, and adopted interventions.

What are the implications for public health practice?

Disentangling different risk factors might contribute to a deeper understanding of the transmission dynamics and ecology of coronavirus disease 2019 and an effective design of monitoring and management strategies.

Characterizing human movement patterns using GPS data loggers in an area of persistent malaria in Zimbabwe along the Mozambique border

BACKGROUND

Human mobility is a driver for the reemergence or resurgence of malaria and has been identified as a source of cross-border transmission. However, movement patterns are difficult to measure in rural areas where malaria risk is high. In countries with malaria elimination goals, it is essential to determine the role of mobility on malaria transmission to implement appropriate interventions.

METHODS

A study was conducted in Mutasa District, Zimbabwe, to investigate human movement patterns in an area of persistent transmission along the Mozambique border. Over 1 year, a convenience sample of 20 participants/month was recruited from active malaria surveillance cohorts to carry an IgotU^® GT-600 global positioning system (GPS) data logger during all daily activities. Consenting participants were tested for malaria at data logger distribution using rapid antigen diagnostic tests and completed a survey questionnaire. GPS data were analyzed using a trajectory analysis tool, and participant movement patterns were characterized throughout the study area and across the border into Mozambique using movement intensity maps, activity space plots, and statistical analyses.

RESULTS

From June 2016-May 2017, 184 participants provided movement tracks encompassing > 350,000 data points and nearly 8000 person-days. Malaria prevalence at logger distribution was 3.7%. Participants traveled a median of 2.8 km/day and spent a median of 4.6 h/day away from home. Movement was widespread within and outside the study area, with participants traveling up to 500 km from their homes. Indices of mobility were higher in the dry season than the rainy season (median km traveled/day = 3.5 vs. 2.2, P = 0.03), among male compared to female participants (median km traveled/day = 3.8 vs. 2.0, P = 0.0008), and among adults compared to adolescents (median total km traveled = 104.6 vs. 59.5, P = 0.05). Half of participants traveled outside the study area, and 30% traveled into Mozambique, including 15 who stayed in Mozambique overnight.

CONCLUSIONS

Study participants in Mutasa District, Zimbabwe, were highly mobile throughout the year. Many participants traveled long distances from home, including overnight trips into Mozambique, with clear implications for malaria control. Interventions targeted at mobile populations and cross-border transmission may be effective in preventing malaria introductions in this region.

Host movement, transmission hot spots, and vector-borne disease dynamics on spatial networks

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.

Development and user testing study of MozzHub: a bipartite network-based dengue hotspot detector

Traditionally, dengue is controlled by fogging, and the prime location for the control measure is at the patient's residence. However, when Malaysia was hit by the first wave of the Coronavirus disease (COVID-19), and the government-imposed movement control order, dengue cases have decreased by more than 30% from the previous year. This implies that residential areas may not be the prime locations for dengue-infected mosquitoes. The existing early warning system was focused on temporal prediction wherein the lack of consideration for spatial component at the microlevel and human mobility were not considered. Thus, we developed MozzHub, which is a web-based application system based on the bipartite network-based dengue model that is focused on identifying the source of dengue infection at a small spatial level (400 m) by integrating human mobility and environmental predictors. The model was earlier developed and validated; therefore, this study presents the design and implementation of the MozzHub system and the results of a preliminary pilot test and user acceptance of MozzHub in six district health offices in Malaysia. It was found that the MozzHub system is well received by the sample of end-users as it was demonstrated as a useful (77.4%), easy-to-operate system (80.6%), and has achieved adequate client satisfaction for its use (74.2%).

A Bayesian modelling framework to quantify multiple sources of spatial variation for disease mapping

Spatial connectivity is an important consideration when modelling infectious disease data across a geographical region. Connectivity can arise for many reasons, including shared characteristics between regions and human or vector movement. Bayesian hierarchical models include structured random effects to account for spatial connectivity. However, conventional approaches require the spatial structure to be fully defined prior to model fitting. By applying penalized smoothing splines to coordinates, we create two-dimensional smooth surfaces describing the spatial structure of the data while making minimal assumptions about the structure. The result is a non-stationary surface which is setting specific. These surfaces can be incorporated into a hierarchical modelling framework and interpreted similarly to traditional random effects. Through simulation studies, we show that the splines can be applied to any symmetric continuous connectivity measure, including measures of human movement, and that the models can be extended to explore multiple sources of spatial structure in the data. Using Bayesian inference and simulation, the relative contribution of each spatial structure can be computed and used to generate hypotheses about the drivers of disease. These models were found to perform at least as well as existing modelling frameworks, while allowing for future extensions and multiple sources of spatial connectivity.

Weather integrated malaria prediction system using Bayesian structural time series model for northeast states of India

Malaria is an endemic disease in India and targeted to eliminate by the year 2030. The present study is aimed at understanding the epidemiological patterns of malaria transmission dynamics in Assam and Arunachal Pradesh followed by the development of a malaria prediction model using monthly climate factors. A total of 144,055 cases in Assam during 2011-2018 and 42,970 cases in Arunachal Pradesh were reported during the 2011-2019 period observed, and Plasmodium falciparum (74.5%) was the most predominant parasite in Assam, whereas Plasmodium vivax (66%) in Arunachal Pradesh. Malaria transmission showed a strong seasonal variation where most of the cases were reported during the monsoon period (Assam, 51.9%, and Arunachal Pradesh, 53.6%). Similarly, the malaria incidence was highest in the male population in both states (Asam, 55.75%, and Arunachal Pradesh, 51.43%), and the disease risk is also higher among the > 15 years age group (Assam, 61.7%, and Arunachal Pradesh, 67.9%). To predict the malaria incidence, Bayesian structural time series (BSTS) and Seasonal Auto-Regressive Integrated Moving Average with eXogenous factors (SARIMAX) models were implemented. A statistically significant association between malaria cases and climate variables was observed. The most influencing climate factors are found to be maximum and mean temperature with a 6-month lag, and it showed a negative association with malaria incidence. The BSTS model has shown superior performance on the optimal auto-correlated dataset (OAD) which contains auto-correlated malaria cases, cross-correlated climate variables besides malaria cases in both Assam (RMSE, 0.106; MAE, 0.089; and SMAPE, 19.2%) and Arunachal Pradesh (RMSE, 0.128; MAE, 0.122; and SMAPE, 22.6%) than the SARIMAX model. The findings suggest that the predictive performance of the BSTS model is outperformed, and it may be helpful for ongoing intervention strategies by governmental and nongovernmental agencies in the northeast region to combat the disease effectively.

Integrating tick density and park visitor behaviors to assess the risk of tick exposure in urban parks on Staten Island, New York

Background

Public green spaces are important for human health, but they may expose visitors to ticks and tick-borne pathogens. We sought to understand, for the first time, visitors’ exposure risk and drivers of tick-preventative behavior in three popular parks on Staten Island, New York City, NY, USA, by integrating tick hazard and park visitors’ behaviors, risk perceptions and knowledge.

Methods

We conducted tick sampling in three parks, across three site types (open spaces, the edge of open spaces, and trails) and three within-park habitats (maintained grass, unmaintained herbaceous, and leaf litter) to estimate tick density during May-August 2019. Human behavior was assessed by observations of time spent and activity type in each site. We integrated the time spent in each location by park visitors and the tick density to estimate the probability of human-tick encounter. To assess visitors’ tick prevention behaviors, a knowledge, attitude, and practices (KAP) survey was administered.

Results

Three tick species (Ixodes scapularis, Amblyomma americanum and Haemaphysalis longicornis) were collected. For all species, the density of nymphs was greatest in unmaintained herbaceous habitats and trails, however, the fewest people entered these hazardous locations. The KAP survey revealed that most respondents (N = 190) identified parks as the main location for tick exposure, but most believed they had minimal risk for tick encounter. Consequently, many visitors did not conduct tick checks. People were most likely to practice tick checks if they knew multiple prevention methods and perceived a high likelihood of tick encounter.

Conclusions

By integrating acarological indices with park visitor behaviors, we found a mismatch between areas with higher tick densities and areas more frequently used by park visitors. However, this exposure risk varied among demographic groups, the type of activities and parks, with a higher probability of human-tick encounters in trails compared to open spaces. Furthermore, we showed that people’s KAP did not change across parks even if parks represented different exposure risks. Our research is a first step towards identifying visitor risk, attitudes, and practices that could be targeted by optimized messaging strategies for tick bite prevention among park visitors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13989-x.

Importance of Public Transport Networks for Reconciling the Spatial Distribution of Dengue and the Association of Socio-Economic Factors with Dengue Risk in Bangkok, Thailand

Dengue is the most widespread mosquito-borne viral disease of man and spreading at an alarming rate. Socio-economic inequality has long been thought to contribute to providing an environment for viral propagation. However, identifying socio-economic (SE) risk factors is confounded by intra-urban daily human mobility, with virus being ferried across cities. This study aimed to identify SE variables associated with dengue at a subdistrict level in Bangkok, analyse how they explain observed dengue hotspots and assess the impact of mobility networks on such associations. Using meteorological, dengue case, national statistics, and transport databases from the Bangkok authorities, we applied statistical association and spatial analyses to identify SE variables associated with dengue and spatial hotspots and the extent to which incorporating transport data impacts the observed associations. We identified three SE risk factors at the subdistrict level: lack of education, % of houses being cement/brick, and number of houses as being associated with increased risk of dengue. Spatial hotspots of dengue were found to occur consistently in the centre of the city, but which did not entirely have the socio-economic risk factor characteristics. Incorporation of the intra-urban transport network, however, much improved the overall statistical association of the socio-economic variables with dengue incidence and reconciled the incongruous difference between the spatial hotspots and the SE risk factors. Our study suggests that incorporating transport networks enables a more real-world analysis within urban areas and should enable improvements in the identification of risk factors.