House-to-house human movement drives dengue virus transmission

Serosurveillance of dengue infection and correlation with mosquito pools for dengue virus positivity during the COVID-19 pandemic in Tamil Nadu, India - A state-wide cross-sectional cluster randomized community-based study

Background

Dengue is a vector-borne viral disease impacting millions across the globe. Nevertheless, akin to many other diseases, reports indicated a decline in dengue incidence and seroprevalence during the COVID-19 pandemic (2020-22). This presumably could be attributed to reduced treatment-seeking rates, under-reporting, misdiagnosis, disrupted health services and reduced exposure to vectors due to lockdowns. Scientific evidence on dengue virus (DENV) disease during the COVID-19 pandemic is limited globally.

Methods

A cross-sectional, randomized cluster sampling community-based survey was carried out to assess anti-dengue IgM and IgG and SARS-CoV-2 IgG seroprevalence across all 38 districts of Tamil Nadu, India. The prevalence of DENV in the Aedes mosquito pools during 2021 was analyzed and compared with previous and following years of vector surveillance for DENV by real-time PCR.

Findings

Results implicate that both DENV-IgM and IgG seroprevalence and mosquito viral positivity were reduced across all the districts. A total of 13464 mosquito pools and 5577 human serum samples from 186 clusters were collected. Of these, 3·76% of mosquito pools were positive for DENV. In the human sera, 4·12% were positive for DENV IgM and 6·4% were positive for DENV IgG. The anti-SARS-CoV-2 antibody titres correlated with dengue seropositivity with a significant association whereas vaccination status significantly correlated with dengue IgM levels.

Interpretation

Continuous monitoring of DENV seroprevalence, especially with the evolving variants of the SARS-CoV-2 virus and surge in COVID-19 cases will shed light on the transmission and therapeutic attributes of dengue infection.

Microclimate factors related to dengue virus burden clusters in two endemic towns of Mexico

In dengue-endemic areas, transmission control is limited by the difficulty of achieving sufficient coverage and sustainability of interventions. To maximize the effectiveness of interventions, areas with higher transmission could be identified and prioritized. The aim was to identify burden clusters of Dengue virus (DENV) infection and evaluate their association with microclimatic factors in two endemic towns from southern Mexico. Information from a prospective population cohort study (2·5 years of follow-up) was used, microclimatic variables were calculated from satellite information, and a cross-sectional design was conducted to evaluate the relationship between the outcome and microclimatic variables in the five surveys. Spatial clustering was observed in specific geographic areas at different periods. Both, land surface temperature (aPR 0·945; IC95% 0·895-0·996) and soil humidity (aPR 3·018; IC95% 1·013-8·994), were independently associated with DENV burden clusters. These findings can help health authorities design focused dengue surveillance and control activities in dengue endemic areas.

Circulation of DENV-2 serotype associated with increased risk of cumulative incidence of severe dengue and dengue with warning signs: A 16-year retrospective study in Peru

Background

Dengue poses a significant public health challenge in Peru and other endemic countries worldwide. While severe dengue is known to be associated with secondary infection at the individual level, the factors that elevate the risk of severe dengue at the population level remain poorly understood. This study leverages over 16 years of secondary data from a Peruvian dengue surveillance system to assess which type of serotype-specific circulation is associated with an increased risk of cumulative incidence of severe dengue or dengue with warning signs (SD-DWS).

Methodology

This is a retrospective analysis of secondary data using the Peruvian Ministry of Health databases of dengue cases and serotyping. A mixed negative binomial regression model for repeated measures over time was employed to estimate the association between the cumulative incidence of reported SD-DWS cases per 100,000 inhabitants and serotype-specific circulation. Crude and adjusted incidence ratios (IRR) were estimated.

Principal findings

The study analyzed data from 2007 to 2022 across 19 regions of Peru, totaling 304 region-years. Data from nearly 58,000 serotype identification reports and 57,966 cases of SD-DWS were analyzed. The regions with most cumulative incidence of SD-DWS per 100,000 inhabitants during 2007 to 2022 were Madre de Dios (3859), Loreto (1518), Ucayali (1492), Tumbes (1335), and Piura (722). The adjusted model revealed a higher risk of cumulative incidence of SD-DWS when there was specific circulation of DENV-123 (aIRR 7.57 CI 4.00 - 14.31), DENV-12 (aIRR 4.66 CI 2.57 - 8.44), DENV-23 (aIRR 3.55 CI 1.75 - 7.21), or when there was circulation of DENV-2 alone or co-circulating with other serotypes (aIRR 27.7 CI 15.46 -49.63).

Conclusions

Circulation of DENV-2 was associated with higher average incidence rate ratios of SD-DWS.

Author summary

We investigated how the circulation of different dengue virus (DENV) serotypes are associated with the incidence of severe dengue and dengue with warning signs in Peru, a country where dengue is endemic. We analyzed 16 years of data from the dengue surveillance system, including nearly 58,000 serotype identification reports and 57,966 cases of severe dengue and dengue with warning signs. We found that regions with specific circulation of DENV-2, either alone or in combination with other serotypes, had higher incidence rates of severe dengue and dengue with warning signs. Our findings highlight the importance of monitoring DENV serotype circulation to manage and prevent severe dengue, especially in regions where DENV-2 is prevalent.

Spatial analysis of dengue transmission in an endemic city in Brazil reveals high spatial structuring on local dengue transmission dynamics

In the last decades, dengue has become one of the most widespread mosquito-borne arboviruses in the world, with an increasing incidence in tropical and temperate regions. The mosquito Aedes aegypti is the dengue primary vector and is more abundant in highly urbanized areas. Traditional vector control methods have showing limited efficacy in sustaining mosquito population at low levels to prevent dengue virus outbreaks. Considering disease transmission is not evenly distributed in the territory, one perspective to enhance vector control efficacy relies on identifying the areas that concentrate arbovirus transmission within an endemic city, i.e., the hotspots. Herein, we used a 13-month timescale during the SARS-Cov-2 pandemic and its forced reduction in human mobility and social isolation to investigate the spatiotemporal association between dengue transmission in children and entomological indexes based on adult Ae. aegypti trapping. Dengue cases and the indexes Trap Positive Index (TPI) and Adult Density Index (ADI) varied seasonally, as expected: more than 51% of cases were notified on the first 2 months of the study, and higher infestation was observed in warmer months. The Moran's Eigenvector Maps (MEM) and Generalized Linear Models (GLM) revealed a strong large-scale spatial structuring in the positive dengue cases, with an unexpected negative correlation between dengue transmission and ADI. Overall, the global model and the purely spatial model presented a better fit to data. Our results show high spatial structure and low correlation between entomological and epidemiological data in Foz do Iguaçu dengue transmission dynamics, suggesting the role of human mobility might be overestimated and that other factors not evaluated herein could be playing a significant role in governing dengue transmission.

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.

Economic optimization of Wolbachia-infected Aedes aegypti release to prevent dengue

BACKGROUND

Dengue virus, primarily transmitted by the Aedes aegypti mosquito, is a major public health concern affecting ≈3.83 billion people worldwide. Recent releases of Wolbachia-transinfected Ae. aegypti in several cities worldwide have shown that it can reduce dengue transmission. However, these releases are costly, and, to date, no framework has been proposed for determining economically optimal release strategies that account for both costs associated with disease risk and releases.

RESULTS

We present a flexible stochastic dynamic programming framework for determining optimal release schedules for Wolbachia-transinfected mosquitoes that balances the cost of dengue infection with the costs of rearing and releasing transinfected mosquitoes. Using an ordinary differential equation model of Wolbachia and dengue in a hypothetical city loosely describing areas at risk of new dengue epidemics, we determined that an all-or-nothing release strategy that quickly brings Wolbachia to fixation is often the optimal solution. Based on this, we examined the optimal facility size, finding that it was inelastic with respect to the mosquito population size, with a 100% increase in population size resulting in a 50-67% increase in optimal facility size. Furthermore, we found that these results are robust to mosquito life-history parameters and are mostly determined by the mosquito population size and the fitness costs associated with Wolbachia.

CONCLUSIONS

These results reinforce that Wolbachia-transinfected mosquitoes can reduce the cost of dengue epidemics. Furthermore, they emphasize the importance of determining the size of the target population and fitness costs associated with Wolbachia before releases occur. © 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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

Aedes-borne pathogens have been increasing in incidence in recent decades despite vector control activities implemented in endemic settings. Vector control for Aedes-transmitted arboviruses typically focuses on households because vectors breed in household containers and bite indoors. Yet, our recent work shows a high abundance of Aedes spp. vectors in public spaces. To investigate the impact of non-household environments on dengue transmission and control, we used field data on the number of water containers and abundance of Aedes mosquitoes in Household (HH) and Non-Household (NH) environments in two Kenyan cities, Kisumu and Ukunda, from 2019-2022. Incorporating information on human activity space, we developed an agent-based model to simulate city-wide conditions considering HH and five types of NH environments in which people move and interact with other humans and vectors during peak biting times. We additionally evaluated the outcome of vector control activities implemented in different environments in preventive (before an epidemic) and reactive (after an epidemic commences) scenarios. We estimated that over half of infections take place in NH environments, where the main spaces for transmission are workplaces, markets, and recreational locations. Accordingly, results highlight the important role of vector control activities at NH locations to reduce dengue. A greater reduction of cases is expected as control activities are implemented earlier, at higher levels of coverage, with greater effectiveness when targeting only NH as opposed to when targeting only HH. Further, local ecological factors such as the differential abundance of water containers within cities are also influential factors to consider for control. This work provides insight into 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.

Mechanisms of Yellow Fever Transmission: Gleaning the Overlooked Records of Importance and Identifying Problems, Puzzles, Serious Issues, Surprises and Research Questions

In viral disease research, few diseases can compete with yellow fever for the volume of literature, historical significance, richness of the topics and the amount of strong interest among both scientists and laypersons. While the major foci of viral disease research shifted to other more pressing new diseases in recent decades, many critically important basic tasks still remain unfinished for yellow fever. Some of the examples include the mechanisms of transmission, the process leading to outbreak occurrence, environmental factors, dispersal, and viral persistence in nature. In this review, these subjects are analyzed in depth, based on information not only in old but in modern literatures, to fill in blanks and to update the current understanding on these topics. As a result, many valuable facts, ideas, and other types of information that complement the present knowledge were discovered. Very serious questions about the validity of the arbovirus concept and some research practices were also identified. The characteristics of YFV and its pattern of transmission that make this virus unique among viruses transmitted by Ae. aegypti were also explored. Another emphasis was identification of research questions. The discovery of a few historical surprises was an unexpected benefit.

Interactions between climate change, urban infrastructure and mobility are driving dengue emergence in Vietnam

Dengue is expanding globally, but how dengue emergence is shaped locally by interactions between climatic and socio-environmental factors is not well understood. Here, we investigate the drivers of dengue incidence and emergence in Vietnam, through analysing 23 years of district-level case data spanning a period of significant socioeconomic change (1998-2020). We show that urban infrastructure factors (sanitation, water supply, long-term urban growth) predict local spatial patterns of dengue incidence, while human mobility is a more influential driver in subtropical northern regions than the endemic south. Temperature is the dominant factor shaping dengue's distribution and dynamics, and using long-term reanalysis temperature data we show that warming since 1950 has expanded transmission risk throughout Vietnam, and most strongly in current dengue emergence hotspots (e.g., southern central regions, Ha Noi). In contrast, effects of hydrometeorology are complex, multi-scalar and dependent on local context: risk increases under either short-term precipitation excess or long-term drought, but improvements in water supply mitigate drought-associated risks except under extreme conditions. Our findings challenge the assumption that dengue is an urban disease, instead suggesting that incidence peaks in transitional landscapes with intermediate infrastructure provision, and provide evidence that interactions between recent climate change and mobility are contributing to dengue's expansion throughout Vietnam.

Understanding the spread of infectious diseases in edge areas of hotspots: dengue epidemics in tropical metropolitan regions

Identifying clusters or hotspots from disease maps is critical in research and practice. Hotspots have been shown to have a higher potential for transmission risk and may be the source of infections, making them a priority for controlling epidemics. However, the role of edge areas of hotspots in disease transmission remains unclear. This study aims to investigate the role of edge areas in disease transmission by examining whether disease incidence rate growth is higher in the edges of disease hotspots during outbreaks. Our data is based on the three most severe dengue epidemic years in Kaohsiung city, Taiwan, from 1998 to 2020. We employed conditional autoregressive (CAR) models and Bayesian areal Wombling methods to identify significant edge areas of hotspots based on the extent of risk difference between adjacent areas. The difference-in-difference (DID) estimator in spatial panel models measures the growth rate of risk by comparing the incidence rate between two groups (hotspots and edge areas) over two time periods. Our results show that in years characterized by exceptionally large-scale outbreaks, the edge areas of hotspots have a more significant increase in disease risk than hotspots, leading to a higher risk of disease transmission and potential disease foci. This finding explains the geographic diffusion mechanism of epidemics, a pattern mixed with expansion and relocation, indicating that the edge areas play an essential role. The study highlights the importance of considering edge areas of hotspots in disease transmission. Furthermore, it provides valuable insights for policymakers and health authorities in designing effective interventions to control large-scale disease outbreaks.

Quantifying the relationship between arboviral infection prevalence and human mobility patterns among participants of the Communities Organized to Prevent Arboviruses cohort (COPA) in southern Puerto Rico

Human movement is increasingly being recognized as a major driver of arbovirus risk and dissemination. The Communities Organized to Prevent Arboviruses (COPA) study is a cohort in southern Puerto Rico to measure arboviral prevalence, evaluate interventions, and collect mobility data. To quantify the relationship between arboviral prevalence and human mobility patterns, we fit multilevel logistic regression models to estimate odds ratios for mobility-related predictors of positive chikungunya IgG or Zika IgM test results collected from COPA, assuming mobility data does not change substantially from year to year. From May 8, 2018-June 8, 2019, 39% of the 1,845 active participants during the study period had a positive arboviral seroprevalence result. Most (74%) participants reported spending five or more weekly hours outside of their home. A 1% increase in weekly hours spent outside the home was associated with a 4% (95% confidence interval (CI): 2-7%) decrease in the odds of testing positive for arbovirus. After adjusting for age and whether a person had air conditioning (AC) at home, any time spent in a work location was protective against arbovirus infection (32% decrease, CI: 9-49%). In fact, there was a general decreased prevalence for individuals who visited locations that were inside and had AC or screens, regardless of the type of location (32% decrease, CI: 12-47%). In this population, the protective characteristics of locations visited appear to be the most important driver of the relationship between mobility and arboviral prevalence. This relationship indicates that not all mobility is the same, with elements like screens and AC providing protection in some locations. These findings highlight the general importance of AC and screens, which are known to be protective against mosquitoes and mosquito-transmitted diseases.

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%.

Projecting the future incidence and burden of dengue in Southeast Asia

The recent global expansion of dengue has been facilitated by changes in urbanisation, mobility, and climate. In this work, we project future changes in dengue incidence and case burden to 2099 under the latest climate change scenarios. We fit a statistical model to province-level monthly dengue case counts from eight countries across Southeast Asia, one of the worst affected regions. We project that dengue incidence will peak this century before declining to lower levels with large variations between and within countries. Our findings reveal that northern Thailand and Cambodia will show the biggest decreases and equatorial areas will show the biggest increases. The impact of climate change will be counterbalanced by income growth, with population growth having the biggest influence on increasing burden. These findings can be used for formulating mitigation and adaptation interventions to reduce the immediate growing impact of dengue virus in the region.

Measuring dengue illness intensity: Development and content validity of the dengue virus daily diary (DENV-DD)

BACKGROUND

Dengue is the most prevalent arboviral infection causing an estimated 50-60 million cases of febrile illness globally per year, exacting considerable disease burden. Few instruments exist to assess the patient illness experience, with most based on healthcare provider assessment, lacking standardization in timepoints and symptom assessment. This study aimed to evaluate the content validity of the novel 'Dengue Virus Daily Diary (DENV-DD)', designed to measure symptom intensity and disease burden within outpatient infant to adult populations.

METHODS

The Dengue Illness Index Report Card was used as a foundation to create the DENV-DD, consisting of patient- and observer-reported outcome (PRO/ObsRO) instruments. In two South American dengue-endemic communities, qualitative combined concept elicitation and cognitive debriefing interviews were conducted among individuals and caregivers of children with symptomatic laboratory-confirmed dengue. Interviews were conducted across two rounds allowing DENV-DD modifications. A small-scale quantitative assessment of the DENV-DD was also conducted with data from an independent Dengue Human Infection Model (DHIM) to generate early evidence of feasibility of DENV-DD completion, instrument performance and insight into the sign/symptom trajectory over the course of illness.

RESULTS

Forty-eight participants were interviewed (20 adults, 20 older children/adolescents with their caregivers, 8 caregivers of younger children). A wide spectrum of signs/symptoms lasting 3-15 days were reported with fever, headache, body ache/pain, loss of appetite, and body weakness each reported by > 70% participants. DENV-DD instructions, items and response scales were understood, and items were considered relevant across ages. DHIM data supported feasibility of DENV-DD completion.

CONCLUSIONS

Findings demonstrate content validity of the DENV-DD (PRO/ObsRO instruments) in dengue-endemic populations. Psychometric and cultural validity studies are ongoing to support use of the DENV-DD in clinical studies.

Predicting the dengue cluster outbreak dynamics in Yogyakarta, Indonesia: a modelling study

Background

Human mobility and climate conditions are recognised key drivers of dengue transmission, but their combined and individual role in the local spatiotemporal clustering of dengue cases is not well understood. This study investigated the effects of human mobility and weather conditions on dengue risk in an urban area in Yogyakarta, Indonesia.

Methods

We established a Bayesian spatiotemporal model for neighbourhood outbreak prediction and evaluated the performances of two different approaches for constructing an adjacency matrix: one based on geographical proximity and the other based on human mobility patterns. We used population, weather conditions, and past dengue cases as predictors using a flexible distributed lag approach. The human mobility data were estimated based on proxies from social media. Unseen data from February 2017 to January 2020 were used to estimate the one-month ahead prediction accuracy of the model.

Findings

When human mobility proxies were included in the spatial covariance structure, the model fit improved in terms of the log score (from 1.748 to 1.561) and the mean absolute error (from 0.676 to 0.522) based on the validation data. Additionally, showed only few observations outside the credible interval of predictions (1.48%) and weather conditions were not found to contribute additionally to the clustering of cases at this scale.

Interpretation

The study shows that it is possible to make highly accurate predictions of the within-city cluster dynamics of dengue using mobility proxies from social media combined with disease surveillance data. These insights are important for proactive and timely outbreak management of dengue.

Funding

Swedish Research Council Formas, Umeå Centre for Global Health Research, Swedish Council for Working Life and Social Research, Swedish research council VINNOVA and Alexander von Humboldt Foundation (Germany).

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.

Arbovirus Transmission Predictions Are Affected by Both Temperature Data Source and Modeling Methodologies across Cities in Colombia

Weather variables has been described as major drivers of vector proliferation and arbovirus transmission. Among them, temperature has consistently been found to be impactful in transmission dynamics, and models that incorporate temperature have been widely used to evaluate and forecast transmission or arboviruses like dengue, zika, or chikungunya virus. Further, there is growing evidence of the importance of micro-environmental temperatures in driving transmission of Aedes aegypti-borne viruses, as these mosquitoes tend to live within domiciles. Yet there is still a considerable gap in our understanding of how accounting for micro-environmental temperatures in models varies from the use of other widely-used, macro-level temperature measures. This effort combines field-collected data of both indoor and outdoor household associated temperatures and weather station temperature data from three Colombian cities to describe the relationship between the measures representing temperature at the micro- and macro-levels. These data indicate that weather station data may not accurately capture the temperature profiles of indoor micro-environments. However, using these data sources, the basic reproductive number for arboviruses was calculated by means of three modeling efforts to investigate whether temperature measure differences translated to differential transmission predictions. Across all three cities, it was determined that the modeling method was more often impactful rather than the temperature data-source, though no consistent pattern was immediately clear. This suggests that temperature data sources and modeling methods are important for precision in arbovirus transmission predictions, and more studies are needed to parse out this complex interaction.

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.

Estimating the impact of the COVID-19 pandemic on dengue in Brazil

Atypical dengue prevalence was observed in 2020 in many dengue-endemic countries, including Brazil. Evidence suggests that the pandemic disrupted not only dengue dynamics due to changes in mobility patterns, but also several aspects of dengue surveillance, such as care seeking behavior, care availability, and monitoring systems. However, we lack a clear understanding of the overall impact on dengue in different parts of the country as well as the role of individual causal drivers. In this study, we estimated the gap between expected and observed dengue cases in 2020 using an interrupted time series design with forecasts from a neural network and a structural Bayesian time series model. We also decomposed the gap into the impacts of climate conditions, pandemic-induced changes in reporting, human susceptibility, and human mobility. We find that there is considerable variation across the country in both overall pandemic impact on dengue and the relative importance of individual drivers. Increased understanding of the causal mechanisms driving the 2020 dengue season helps mitigate some of the data gaps caused by the COVID-19 pandemic and is critical to developing effective public health interventions to control dengue in the future.

Residual efficacy of the neonicotinoid insecticide clothianidin against pyrethroid-resistant Aedes aegypti

BACKGROUND

Here we report the residual efficacy of the neonicotinoid insecticide clothianidin against pyrethroid-resistant Aedes aegypti. We first conducted a range-finding evaluation of clothianidin on three different substrates (wall, wood, cloth) using three doses (100, 300 and 600 mg a.i. m-2 ) and conducting World Health Organization (WHO) cone bioassays to assess acute (24 h) and delayed (up to 7 days) mortality. In experimental houses located in Merida (Mexico) and using free-flying pyrethroid-resistant Ae. aegypti females, we quantified the acute and delayed mortality after a 24-h exposure to the targeted indoor residual spraying (TIRS) of two clothianidin doses (100 and 300 mg a.i. m-2 ).

RESULTS

Range-finding studies with WHO cones showed low (<50%) acute mortality for all surfaces, doses and times post spraying. Delayed mortality was higher, with average values above or close to the 60% mark (and 95% confidence interval estimates crossing 80% for the 600 mg a.i. m-2 dose). In experimental houses, a similar low acute mortality was quantified (range of mortality across 12 months was 2-44% for 100 mg a.i. m-2 and 8-61% for 300 mg a.i/m2 ). However, delayed mortality showed a strong effect of clothianidin on free-flying Ae. aegypti, with values above 80% up to 7 months post-TIRS.

CONCLUSION

Novel residual insecticide molecules have a promising outlook for Ae. aegypti control and can contribute to the expansion and adoption of TIRS in urban areas. clothianidin can contribute to the control of resistant Ae. aegypti and provide residual control for up to 7 months after application. © 2022 Society of Chemical Industry.

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.

An intelligent healthcare system for predicting and preventing dengue virus infection

Dengue is a mosquito-borne pandemic viral infection, which transmits to humans from Female Aedes albopictis or Aedes agypti mosquitoes. It progressively deteriorates the health of infected individuals and poses a high threat of human morbidity and mortality. This paper proposes an intelligent healthcare system which identifies, monitors, and alerts dengue virus (DeV) infected individuals and other stakeholders in real-time and control the DeV infection outbreak using cloud computing, internet of things and fog computing paradigms. The proposed system uses Naive Bayesian Network (NBN) for diagnosing the possibly DeV infected individuals and generating real-time alerts for suggesting and alerting the concerned stakeholders for taking on-time necessary actions at the fog subsystem. The proposed system also uses Social Network Analysis at the cloud subsystem, to provide Global Positioning Systems (GPS)-based global risk assessment of the DeV infection on Google Maps (Google-based web map service) and control DeV infection outbreak. The analysis of the experimental results acknowledges the efficiency of the NBN-based DeV infection diagnosis, alert generation, and GPS-based risk assessment functionality, of the proposed system, via various statistical measures and experimental approaches.

Quantifying heterogeneities in arbovirus transmission: Description of the rationale and methodology for a prospective longitudinal study of dengue and Zika virus transmission in Iquitos, Peru (2014-2019)

Current knowledge of dengue virus (DENV) transmission provides only a partial understanding of a complex and dynamic system yielding a public health track record that has more failures than successes. An important part of the problem is that the foundation for contemporary interventions includes a series of longstanding, but untested, assumptions based on a relatively small portion of the human population; i.e., people who are convenient to study because they manifest clinically apparent disease. Approaching dengue from the perspective of people with overt illness has produced an extensive body of useful literature. It has not, however, fully embraced heterogeneities in virus transmission dynamics that are increasingly recognized as key information still missing in the struggle to control the most important insect-transmitted viral infection of humans. Only in the last 20 years have there been significant efforts to carry out comprehensive longitudinal dengue studies. This manuscript provides the rationale and comprehensive, integrated description of the methodology for a five-year longitudinal cohort study based in the tropical city of Iquitos, in the heart of the Peruvian Amazon. Primary data collection for this study was completed in 2019. Although some manuscripts have been published to date, our principal objective here is to support subsequent publications by describing in detail the structure, methodology, and significance of a specific research program. Our project was designed to study people across the entire continuum of disease, with the ultimate goal of quantifying heterogeneities in human variables that affect DENV transmission dynamics and prevention. Because our study design is applicable to other Aedes transmitted viruses, we used it to gain insights into Zika virus (ZIKV) transmission when during the project period ZIKV was introduced and circulated in Iquitos. Our prospective contact cluster investigation design was initiated by detecttion of a person with a symptomatic DENV infection and then followed that person's immediate contacts. This allowed us to monitor individuals at high risk of DENV infection, including people with clinically inapparent and mild infections that are otherwise difficult to detect. We aimed to fill knowledge gaps by defining the contribution to DENV transmission dynamics of (1) the understudied majority of DENV-infected people with inapparent and mild infections and (2) epidemiological, entomological, and socio-behavioral sources of heterogeneity. By accounting for factors underlying variation in each person's contribution to transmission we sought to better determine the type and extent of effort needed to better prevent virus transmission and disease.

A phylogenetic study of dengue virus in urban Vietnam shows long-term persistence of endemic strains

Dengue virus (DENV) causes repeated outbreaks of disease in endemic areas, with patterns of local transmission strongly influenced by seasonality, importation via human movement, immunity, and vector control efforts. An understanding of how each of these interacts to enable endemic transmission (continual circulation of local virus strains) is largely unknown. There are times of the year when no cases are reported, often for extended periods of time, perhaps wrongly implying the successful eradication of a local strain from that area. Individuals who presented at a clinic or hospital in four communes in Nha Trang, Vietnam, were initially tested for DENV antigen presence. Enrolled positive individuals then had their corresponding household members invited to participate, and those who enrolled were tested for DENV. The presence of viral nucleic acid in all samples was confirmed using quantitative polymerase chain reaction, and positive samples were then whole-genome sequenced using an amplicon and target enrichment library preparation techniques and Illumina MiSeq sequencing technology. Generated consensus genome sequences were then analysed using phylogenetic tree reconstruction to categorise sequences into clades with a common ancestor, enabling investigations of both viral clade persistence and introductions. Hypothetical introduction dates were additionally assessed using a molecular clock model that calculated the time to the most recent common ancestor (TMRCA). We obtained 511 DENV whole-genome sequences covering four serotypes and more than ten distinct viral clades. For five of these clades, we had sufficient data to show that the same viral lineage persisted for at least several months. We noted that some clades persisted longer than others during the sampling time, and by comparison with other published sequences from elsewhere in Vietnam and around the world, we saw that at least two different viral lineages were introduced into the population during the study period (April 2017-2019). Next, by inferring the TMRCA from the construction of molecular clock phylogenies, we predicted that two of the viral lineages had been present in the study population for over a decade. We observed five viral lineages co-circulating in Nha Trang from three DENV serotypes, with two likely to have remained as uninterrupted transmission chains for a decade. This suggests clade cryptic persistence in the area, even during periods of low reported incidence.

A critical assessment of the detailed Aedes aegypti simulation model Skeeter Buster 2 using field experiments of indoor insecticidal control in Iquitos, Peru

The importance of mosquitoes in human pathogen transmission has motivated major research efforts into mosquito biology in pursuit of more effective vector control measures. Aedes aegypti is a particular concern in tropical urban areas, where it is the primary vector of numerous flaviviruses, including the yellow fever, Zika, and dengue viruses. With an anthropophilic habit, Ae. aegypti prefers houses, human blood meals, and ovipositioning in water-filled containers. We hypothesized that this relatively simple ecological niche should allow us to predict the impacts of insecticidal control measures on mosquito populations. To do this, we use Skeeter Buster 2 (SB2), a stochastic, spatially explicit, mechanistic model of Ae. aegypti population biology. SB2 builds on Skeeter Buster, which reproduced equilibrium dynamics of Ae. aegypti in Iquitos, Peru. Our goal was to validate SB2 by predicting the response of mosquito populations to perturbations by indoor insecticidal spraying and widespread destructive insect surveys. To evaluate SB2, we conducted two field experiments in Iquitos, Peru: a smaller pilot study in 2013 (S-2013) followed by a larger experiment in 2014 (L-2014). Here, we compare model predictions with (previously reported) empirical results from these experiments. In both simulated and empirical populations, repeated spraying yielded substantial yet temporary reductions in adult densities. The proportional effects of spraying were broadly comparable between simulated and empirical results, but we found noteworthy differences. In particular, SB2 consistently over-estimated the proportion of nulliparous females and the proportion of containers holding immature mosquitoes. We also observed less temporal variation in simulated surveys of adult abundance relative to corresponding empirical observations. Our results indicate the presence of ecological heterogeneities or sampling processes not effectively represented by SB2. Although additional empirical research could further improve the accuracy and precision of SB2, our results underscore the importance of non-linear dynamics in the response of Ae. aegypti populations to perturbations, and suggest general limits to the fine-grained predictability of its population dynamics over space and time.

Preventive residual insecticide applications successfully controlled Aedes aegypti in Yucatan, Mexico

Insecticide-based approaches remain a key pillar for Aedes-borne virus (ABV, dengue, chikungunya, Zika) control, yet they are challenged by the limited effect of traditional outdoor insecticide campaigns responding to reported arboviral cases and by the emergence of insecticide resistance in mosquitoes. A three-arm Phase II unblinded entomological cluster randomized trial was conducted in Merida, Yucatan State, Mexico, to quantify the entomological impact of targeted indoor residual spraying (TIRS, application of residual insecticides in Ae. aegypti indoor resting sites) applied preventively 2 months before the beginning of the arbovirus transmission season. Trial arms involved the use of two insecticides with unrelated modes of action (Actellic 300CS, pirimiphos-methyl, and SumiShield 50WG, clothianidin) and a control arm where TIRS was not applied. Entomological impact was quantified by Prokopack adult collections performed indoors during 10 min per house. Regardless of the insecticide, conducting a preventive TIRS application led to significant reductions in indoor Ae. aegypti densities, which were maintained at the same levels as in the low arbovirus transmission period (Actellic 300CS reduced Ae. aegypti density up to 8 months, whereas SumiShield 50WG up to 6 months). The proportional reduction in Ae. aegypti abundance in treatment houses compared to control houses was 50-70% for Actellic 300CS and 43-63% for SumiShield 50WG. Total operational costs including insecticide ranged from US$4.2 to US$10.5 per house, depending on the insecticide cost. Conducting preventive residual insecticide applications can maintain Ae. aegypti densities at low levels year-round with important implications for preventing ABVs in the Americas and beyond.

The effect of spatial dynamics on the behaviour of an environmentally transmitted disease

Understanding the spread of pathogens through the environment is critical to a fuller comprehension of disease dynamics. However, many mathematical models of disease dynamics ignore spatial effects. We seek to expand knowledge around the interaction between the bare-nosed wombat (Vombatus ursinus) and sarcoptic mange (etiologic agent Sarcoptes scabiei), by extending an aspatial mathematical model to include spatial variation. S. scabiei was found to move through our modelled region as a spatio-temporal travelling wave, leaving behind pockets of localized host extinction, consistent with field observations. The speed of infection spread was also comparable with field research. Our model predicts that the inclusion of spatial dynamics leads to the survival and recovery of affected wombat populations when an aspatial model predicts extinction. Collectively, this research demonstrates how environmentally transmitted S. scabiei can result in travelling wave dynamics, and that inclusion of spatial variation reveals a more resilient host population than aspatial modelling approaches.

What Heterogeneities in Individual-level Mobility Are Lost During Aggregation? Leveraging GPS Logger Data to Understand Fine-scale and Aggregated Patterns of Mobility

Human movement drives spatial transmission patterns of infectious diseases. Population-level mobility patterns are often quantified using aggregated data sets, such as census migration surveys or mobile phone data. These data are often unable to quantify individual-level travel patterns and lack the information needed to discern how mobility varies by demographic groups. Individual-level datasets can capture additional, more precise, aspects of mobility that may impact disease risk or transmission patterns and determine how mobility differs across cohorts; however, these data are rare, particularly in locations such as sub-Saharan Africa. Using detailed GPS logger data collected from three sites in southern Africa, we explore metrics of mobility such as percent time spent outside home, number of locations visited, distance of locations, and time spent at locations to determine whether they vary by demographic, geographic, or temporal factors. We further create a composite mobility score to identify how well aggregated summary measures would capture the full extent of mobility patterns. Although sites had significant differences in all mobility metrics, no site had the highest mobility for every metric, a distinction that was not captured by the composite mobility score. Further, the effects of sex, age, and season on mobility were all dependent on site. No factor significantly influenced the number of trips to locations, a common way to aggregate datasets. When collecting and analyzing human mobility data, it is difficult to account for all the nuances; however, these analyses can help determine which metrics are most helpful and what underlying differences may be present.

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%).

Etiologies of Acute Undifferentiated Febrile Illnesses in and near Iquitos from 1993 to 1999 in the Amazon River Basin of Peru

The objective of this study was to determine the etiology of febrile illnesses among patients from October 1, 1993 through September 30, 1999, in the urban community of Iquitos in the Amazon River Basin of Peru. Epidemiological and clinical data as well as blood samples were obtained from consenting patients at hospitals, health clinics and private residences. Samples were tested for arboviruses in cell cultures and for IgM and IgG antibodies by ELISA. Blood smears were examined for malaria, and sera were tested for antibodies to Leptospira spp. by ELISA and microscopic agglutination. Among 6,607 febrile patients studied, dengue viruses caused 14.6% of the cases, and Venezuelan equine encephalitis virus caused 2.5%, Oropouche virus 1.0%, Mayaro virus 0.4%, and other arboviruses caused 0.2% of the cases. Also, 22.9% of 4,844 patients tested were positive for malaria, and of 400 samples tested, 9% had evidence of acute leptospirosis. Although the study was not designed to assess the importance of these pathogens as a cause of human morbidity in the total population, these results indicate that arboviruses, leptospirosis, and malaria were the cause of approximately 50% of the febrile cases. Although the arboviruses that were diagnosed can produce asymptomatic infections, our findings increased the overall understanding of the relative health burden of these infections, as well as baseline knowledge needed for designing and implementing further studies to better assess the health impact and threat of these pathogens in the Amazon Basin of Peru.

Spatio-temporal dynamics of three diseases caused by Aedes-borne arboviruses in Mexico

Background

The intensity of transmission of Aedes-borne viruses is heterogeneous, and multiple factors can contribute to variation at small spatial scales. Illuminating drivers of heterogeneity in prevalence over time and space would provide information for public health authorities. The objective of this study is to detect the spatiotemporal clusters and determine the risk factors of three major Aedes-borne diseases, Chikungunya virus (CHIKV), Dengue virus (DENV), and Zika virus (ZIKV) clusters in Mexico.

Methods

We present an integrated analysis of Aedes-borne diseases (ABDs), the local climate, and the socio-demographic profiles of 2469 municipalities in Mexico. We used SaTScan to detect spatial clusters and utilize the Pearson correlation coefficient, Randomized Dependence Coefficient, and SHapley Additive exPlanations to analyze the influence of socio-demographic and climatic factors on the prevalence of ABDs. We also compare six machine learning techniques, including XGBoost, decision tree, Support Vector Machine with Radial Basis Function kernel, K nearest neighbors, random forest, and neural network to predict risk factors of ABDs clusters.

Results

DENV is the most prevalent of the three diseases throughout Mexico, with nearly 60.6% of the municipalities reported having DENV cases. For some spatiotemporal clusters, the influence of socio-economic attributes is larger than the influence of climate attributes for predicting the prevalence of ABDs. XGBoost performs the best in terms of precision-measure for ABDs prevalence.

Conclusions

Both socio-demographic and climatic factors influence ABDs transmission in different regions of Mexico. Future studies should build predictive models supporting early warning systems to anticipate the time and location of ABDs outbreaks and determine the stand-alone influence of individual risk factors and establish causal mechanisms.

Dengue Incidence and Aedes Vector Collections in Relation to COVID-19 Population Mobility Restrictions

Contrary to expectation, dengue incidence decreased in many countries during the period when stringent population movement restrictions were imposed to combat COVID-19. Using a seasonal autoregressive integrated moving average model, we previously reported a 74% reduction in the predicted number of dengue cases from March 2020 to April 2021 in the whole of Sri Lanka, with reductions occurring in all 25 districts in the country. The reduction in dengue incidence was accompanied by an 87% reduction in larval collections of Aedes vectors in the northern city of Jaffna. It was proposed that movement restrictions led to reduced human contact and blood feeding by Aedes vectors, accompanied by decreased oviposition and vector densities, which were responsible for diminished dengue transmission. These findings are extended in the present study by investigating the relationship between dengue incidence, population movement restrictions, and vector larval collections between May 2021 and July 2022, when movement restrictions began to be lifted, with their complete removal in November 2021. The new findings further support our previous proposal that population movement restrictions imposed during the COVID-19 pandemic reduced dengue transmission primarily by influencing human–Aedes vector interaction dynamics.

How do i bite thee? let me count the ways: Exploring the implications of individual biting habits of Aedes aegypti for dengue transmission

In models of mosquito-borne transmission, the mosquito biting rate is an influential parameter, and understanding the heterogeneity of the process of biting is important, as biting is usually assumed to be relatively homogeneous across individuals, with time-between-bites described by an exponentially distributed process. However, these assumptions have not been addressed through laboratory experimentation. We experimentally investigated the daily biting habits of Ae. aegypti at three temperatures (24°C, 28°C, and 32°C) and determined that there was individual heterogeneity in biting habits (number of bites, timing of bites, etc.). We further explored the consequences of biting heterogeneity using an individual-based model designed to examine whether a particular biting profile determines whether a mosquito is more or less likely to 1) become exposed given a single index case of dengue (DENV) and 2) transmit to a susceptible human individual. Our experimental results indicate that there is heterogeneity among individuals and among temperature treatments. We further show that this results in altered probabilities of transmission of DENV to and from individual mosquitoes based on biting profiles. While current model representation of biting may work under some conditions, it might not uniformly be the best fit for this process. Our data also confirm that biting is a non-monotonic process with temperatures around 28°C being optimum.

Global Change and Emerging Infectious Diseases

Our world is undergoing rapid planetary changes driven by human activities, often mediated by economic incentives and resource management, affecting all life on Earth. Concurrently, many infectious diseases have recently emerged or spread into new populations. Mounting evidence suggests that global change-including climate change, land-use change, urbanization, and global movement of individuals, species, and goods-may be accelerating disease emergence by reshaping ecological systems in concert with socioeconomic factors. Here, we review insights, approaches, and mechanisms by which global change drives disease emergence from a disease ecology perspective. We aim to spur more interdisciplinary collaboration with economists and identification of more effective and sustainable interventions to prevent disease emergence. While almost all infectious diseases change in response to global change, the mechanisms and directions of these effects are system specific, requiring new, integrated approaches to disease control that recognize linkages between environmental and economic sustainability and human and planetary health.

Geographical clusters of dengue outbreak in Singapore during the Covid-19 nationwide lockdown of 2020

Dengue, a mosquito-transmitted viral disease, has posed a public health challenge to Singaporean residents over the years. In 2020, Singapore experienced an unprecedented dengue outbreak. We collected a dataset of geographical dengue clusters reported by the National Environment Agency (NEA) from 15 February to 9 July in 2020, covering the nationwide lockdown associated with Covid-19 during the period from 7 April to 1 June. NEA regularly updates the dengue clusters during which an infected person may be tagged to one cluster based on the most probable infection location (residential apartment or workplace address), which is further matched to fine-grained spatial units with an average coverage of about 1.35 km². Such dengue cluster dataset helps not only reveal the dengue transmission patterns, but also reflect the effects of lockdown on dengue spreading dynamics. The resulting data records are released in simple formats for easy access to facilitate studies on dengue epidemics.

Measurement(s)	dengue infection locations
Technology Type(s)	NEA’s disclosured report
Factor Type(s)	Singapore’s dengue in in 2020

Urban mobility patterns and the spatial distribution of infections in Santiago de Chile

The process of a virus spread is inherently spatial. Even though Latin America became the epicenter of the COVID-19 pandemic in May 2020, there is still little evidence of the relationship between urban mobility and virus propagation in the region. This paper combines network analysis of mobility patterns in public transportation with a spatial error correction model for Santiago de Chile. Results indicate that a 10% higher number of daily public transportation trips received by an administrative unit in the city was associated with a 1.3% higher number of confirmed COVID-19 cases per 100,000 inhabitants. Following these findings, we propose an empirical method to identify and classify neighborhoods according to the level and type of risk for COVID-19-like disease propagation, helping policymakers manage mobility during the initial stages of an epidemic outbreak.

Epidemiological Characteristics and the Dynamic Transmission Model of Dengue Fever in Zhanjiang City, Guangdong Province in 2018

Background: With the progress of urbanization, the mobility of people has gradually increased, which has led to the further spread of dengue fever. This study evaluated the transmissibility of dengue fever within districts and between different districts in Zhanjiang City to provide corresponding advice for cross-regional prevention and control. Methods: A mathematical model of transmission dynamics was developed to explore the transmissibility of the disease and to compare that between different regions. Results: A total of 467 DF cases (6.38 per 100,000 people) were reported in Zhanjiang City in 2018. In the model, without any intervention, the number of simulated cases in this epidemic reached about 950. The dengue fever transmissions between districts varied within and between regions. When the spread of dengue fever from Chikan Districts to other districts was cut off, the number of cases in other districts dropped significantly or even to zero. When the density of mosquitoes in Xiashan District was controlled, the dengue fever epidemic in Xiashan District was found to be significantly alleviated. Conclusions: When there is a dengue outbreak, timely measures can effectively control it from developing into an epidemic. Different prevention and control measures in different districts could efficiently reduce the risk of disease transmission.

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.

A cross-sectional study to assess the epidemiological situation and associated risk factors of dengue fever; knowledge, attitudes, and practices about dengue prevention in Khyber Pakhtunkhwa Province, Pakistan

Background

Dengue fever has been responsible for around 12 countrywide large outbreaks in Pakistan, resulting in 286,262 morbidities and 1,108 deaths. Khyber Pakhtunkhwa (KP) is the most recently impacted province. This study aimed to investigate the molecular, epidemiological, and potential elements that contribute to increasing dengue transmission patterns, and knowledge, attitude, and practice (KAP) toward dengue in KP province.

Method

This cross-sectional community-based study was conducted (June-December, 2021) in two phases. Phase I involved the epidemiological (n = 5,242) and molecular analysis of DENV in 500 randomly collected blood samples of the 2021 dengue outbreak in KP. Phase II focused on assessing dengue-KAP levels in healthy communities (n = 14,745, aged >18 years), adopting a cross-sectional clustered multistage sampling in eight districts (dengue-hotspot vs. non-hotspot) of KP. Chi-square tests and logistic regression analysis were applied.

Results

Peshawar district had the highest dengue cases (60.0%) associated with the predominant co-circulation of DENV-2 (45.8%) and DENV-3 (50.4%) serotypes. A rise in cases was reported in October (41.8%) followed by September (27.9%) and August (14.4%; p < 0.001). Males (63.7%, p < 0.001) and individuals aged 16–30 years (37.0%, p < 0.001) were highly affected. General workers (18.0%), families with a monthly income of 10,000–20,000 Pak rupees (50.5%), unmarried (71.0%), uneducated (31%), families with higher human density (>10 individuals per household), and those (29.0%) who faced power outages for more than 7/24 h were the most affected. Moreover, co-morbidities like renal failure and bronchial asthma were associated with disease severity. A community survey on KAP revealed that an average of 74, 60, and 43% of the participants demonstrated good knowledge, attitudes, and dengue preventive practices, respectively.

Conclusion

Multiple poor socioeconomic elements are influencing dengue fever transmission in the province. Higher KAP levels may explain the low frequency of dengue in non-hotspot districts. Our study emphasizes the need for effective and long-term public health education, strengthened vector surveillance, and expanded laboratory capacity for better diagnosis and management of dengue cases to better predict the burden and seasonality of disease in the country.

Disruption of spatiotemporal clustering in dengue cases by wMel Wolbachia in Yogyakarta, Indonesia

Dengue exhibits focal clustering in households and neighborhoods, driven by local mosquito population dynamics, human population immunity, and fine scale human and mosquito movement. We tested the hypothesis that spatiotemporal clustering of homotypic dengue cases is disrupted by introduction of the arbovirus-blocking bacterium Wolbachia (wMel-strain) into the Aedes aegypti mosquito population. We analysed 318 serotyped and geolocated dengue cases (and 5921 test-negative controls) from a randomized controlled trial in Yogyakarta, Indonesia of wMel deployments. We find evidence of spatial clustering up to 300 m among the 265 dengue cases (3083 controls) in the untreated trial arm. Participant pairs enrolled within 30 days and 50 m had a 4.7-fold increase (compared to 95% CI on permutation-based null distribution: 0.1, 1.2) in the odds of being homotypic (i.e. potentially transmission-related) as compared to pairs occurring at any distance. In contrast, we find no evidence of spatiotemporal clustering among the 53 dengue cases (2838 controls) resident in the wMel-treated arm. Introgression of wMel Wolbachia into Aedes aegypti mosquito populations interrupts focal dengue virus transmission leading to reduced case incidence; the true intervention effect may be greater than the 77% efficacy measured in the primary analysis of the Yogyakarta trial.

A longitudinal study of the impact of university student return to campus on the SARS-CoV-2 seroprevalence among the community members

Returning university students represent large-scale, transient demographic shifts and a potential source of transmission to adjacent communities during the COVID-19 pandemic. In this prospective longitudinal cohort study, we tested for IgG antibodies against SARS-CoV-2 in a non-random cohort of residents living in Centre County prior to the Fall 2020 term at the Pennsylvania State University and following the conclusion of the Fall 2020 term. We also report the seroprevalence in a non-random cohort of students collected at the end of the Fall 2020 term. Of 1313 community participants, 42 (3.2%) were positive for SARS-CoV-2 IgG antibodies at their first visit between 07 August and 02 October 2020. Of 684 student participants who returned to campus for fall instruction, 208 (30.4%) were positive for SARS-CoV-2 antibodies between 26 October and 21 December. 96 (7.3%) community participants returned a positive IgG antibody result by 19 February. Only contact with known SARS-CoV-2-positive individuals and attendance at small gatherings (20-50 individuals) were significant predictors of detecting IgG antibodies among returning students (aOR, 95% CI 3.1, 2.07-4.64; 1.52, 1.03-2.24; respectively). Despite high seroprevalence observed within the student population, seroprevalence in a longitudinal cohort of community residents was low and stable from before student arrival for the Fall 2020 term to after student departure. The study implies that heterogeneity in SARS-CoV-2 transmission can occur in geographically coincident populations.

Effects of COVID-19 Non-Pharmacological Interventions on Dengue Infection: A Systematic Review and Meta-Analysis

Non-pharmacological interventions (NPIs) implemented during the coronavirus disease 2019 (COVID-19) pandemic have demonstrated significant positive effects on other communicable diseases. Nevertheless, the response for dengue fever has been mixed. To illustrate the real implications of NPIs on dengue transmission and to determine the effective measures for preventing and controlling dengue, we performed a systematic review and meta-analysis of the available global data to summarize the effects comprehensively. We searched Embase, PubMed, and Web of Science in line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines from December 31, 2019, to March 30, 2022, for studies of NPI efficacy on dengue infection. We obtained the annual reported dengue cases from highly dengue-endemic countries in 2015–2021 from the European Centre for Disease Prevention and Control to determine the actual change in dengue cases in 2020 and 2021, respectively. A random-effects estimate of the pooled odds was generated with the Mantel-Haenszel method. Between-study heterogeneity was assessed using the inconsistency index (I²) and subgroup analysis according to country (dengue-endemic or non-endemic) was conducted. This review was registered with PROSPERO (CRD42021291487). A total of 17 articles covering 32 countries or regions were included in the review. Meta-analysis estimated a pooled relative risk of 0.39 (95% CI: 0.28–0.55), and subgroup revealed 0.06 (95% CI: 0.02-0.25) and 0.55 (95% CI: 0.44-0.68) in dengue non-endemic areas and dengue-endemic countries, respectively, in 2020. The majority of highly dengue-endemic countries in Asia and Americas reported 0–100% reductions in dengue cases in 2020 compared to previous years, while some countries (4/20) reported a dramatic increase, resulting in an overall increase of 11%. In contrast, there was an obvious reduction in dengue cases in 2021 in almost all countries (18/20) studied, with an overall 40% reduction rate. The overall effectiveness of NPIs on dengue varied with region and time due to multiple factors, but most countries reported significant reductions. Travel-related interventions demonstrated great effectiveness for reducing imported cases of dengue fever. Internal movement restrictions of constantly varying intensity and range are more likely to mitigate the entire level of dengue transmission by reducing the spread of dengue fever between regions within a country, which is useful for developing a more comprehensive and sustainable strategy for preventing and controlling dengue fever in the future.

Distance to public transit predicts spatial distribution of dengue virus incidence in Medellín, Colombia

Dengue is a growing global threat in some of the world’s most rapidly growing landscapes. Research shows that urbanization and human movement affect the spatial dynamics and magnitude of dengue outbreaks; however, precise effects of urban growth on dengue are not well understood because of a lack of sufficiently fine-scaled data. We analyzed nine years of address-level dengue case data in Medellin, Colombia during a period of public transit expansion. We correlate changes in the spread and magnitude of localized outbreaks to changes in accessibility and usage of public transit. Locations closer to and with a greater utilization of public transit had greater dengue incidence. This relationship was modulated by socioeconomic status; lower socioeconomic status locations experienced stronger effects of public transit accessibility and usage on dengue incidence. Public transit is a vital urban resource, particularly among low socioeconomic populations. These results highlight the importance of public health services concurrent with urban growth.

Mobility evaluation by GPS tracking in a rural, low-income population in Cambodia

Global Positioning System (GPS) technology is an effective tool for quantifying individuals' mobility patterns and can be used to understand their influence on infectious disease transmission. In Cambodia, mobility measurements have been limited to questionnaires, which are of limited efficacy in rural environments. In this study, we used GPS tracking to measure the daily mobility of Cambodian forest goers, a population at high risk of malaria, and developed a workflow adapted to local constraints to produce an optimal dataset representative of the participants' mobility. We provide a detailed assessment of the GPS tracking and analysis of the data, and highlight the associated difficulties to facilitate the implementation of similar studies in the future.

Language and the cultural markers of COVID-19

Despite its universal nature, the impact of COVID-19 has not been geographically homogeneous. While certain countries and regions have been severely affected, registering record infection rates and excess deaths, others experienced only milder outbreaks. We investigate to what extent human factors, in particular cultural origins reflected in different attitudes and behavioural norms, can explain different degrees of exposure to the virus. Motivated by the linguistic relativity hypothesis, we take language as a proxy for cultural origins and exploit the exogenous variation in the language spoken around the border that divides the French- and German-speaking parts of Switzerland to estimate the impact of culture on exposure to COVID-19. The results obtained using a spatial regression discontinuity design reveal, that within 50- and 25- kilometres bandwidth from the language border, the average COVID-19 exposure levels for individuals in French speaking municipalities was higher. In particular, we find that German speaking municipalities were associated with a reduction of around 40% - 50% in the odds of COVID-19 exposure compared to the French speaking municipalities.