House-to-house human movement drives dengue virus transmission

A spatial model of socioeconomic and environmental determinants of dengue fever in Cali, Colombia

Dengue fever has gradually re-emerged across the global South, particularly affecting urban areas of the tropics and sub-tropics. The dynamics of dengue fever transmission are sensitive to changes in environmental conditions, as well as local demographic and socioeconomic factors. In 2010, the municipality of Cali, Colombia, experienced one of its worst outbreaks, however the outbreak was not spatially homogeneous across the city. In this paper, we evaluate the role of socioeconomic and environmental factors associated with this outbreak at the neighborhood level, using a Geographically Weighted Regression model. Key socioeconomic factors include population density and socioeconomic stratum, whereas environmental factors are proximity to both tire shops and plant nurseries and the presence of a sewage system (R²=0.64). The strength of the association between these factors and the incidence of dengue fever is spatially heterogeneous at the neighborhood level. The findings provide evidence to support public health strategies in allocating resources locally, which will enable a better detection of high risk areas, a reduction of the risk of infection and to strengthen the resilience of the population.

Risk assessment of dengue fever in Zhongshan, China: a time-series regression tree analysis

Dengue fever (DF) is the most prevalent and rapidly spreading mosquito-borne disease globally. Control of DF is limited by barriers to vector control and integrated management approaches. This study aimed to explore the potential risk factors for autochthonous DF transmission and to estimate the threshold effects of high-order interactions among risk factors. A time-series regression tree model was applied to estimate the hierarchical relationship between reported autochthonous DF cases and the potential risk factors including the timeliness of DF surveillance systems (median time interval between symptom onset date and diagnosis date, MTIOD), mosquito density, imported cases and meteorological factors in Zhongshan, China from 2001 to 2013. We found that MTIOD was the most influential factor in autochthonous DF transmission. Monthly autochthonous DF incidence rate increased by 36·02-fold [relative risk (RR) 36·02, 95% confidence interval (CI) 25·26–46·78, compared to the average DF incidence rate during the study period] when the 2-month lagged moving average of MTIOD was >4·15 days and the 3-month lagged moving average of the mean Breteau Index (BI) was ⩾16·57. If the 2-month lagged moving average MTIOD was between 1·11 and 4·15 days and the monthly maximum diurnal temperature range at a lag of 1 month was <9·6 °C, the monthly mean autochthonous DF incidence rate increased by 14·67-fold (RR 14·67, 95% CI 8·84–20·51, compared to the average DF incidence rate during the study period). This study demonstrates that the timeliness of DF surveillance systems, mosquito density and diurnal temperature range play critical roles in the autochthonous DF transmission in Zhongshan. Better assessment and prediction of the risk of DF transmission is beneficial for establishing scientific strategies for DF early warning surveillance and control.

The Epidemiological Characteristics and Dynamic Transmission of Dengue in China, 2013

Background

There was a dengue epidemic in several regions of China in 2013. No study has explored the dynamics of dengue transmission between different geographical locations with dengue outbreaks in China. The purpose of the study is to analyze the epidemiological characteristics and to explore the dynamic transmission of dengue in China, 2013.

Methodology and Principal Findings

Records of dengue cases of 2013 were obtained from the China Notifiable Disease Surveillance System. Full E-gene sequences of dengue virus detected from the outbreak regions of China were download from GenBank. Geographical Information System and heatmaps were used to describe the epidemiological characteristics. Maximum Likelihood phylogenetic and Bayesian phylogeographic analyses were conducted to explore the dengue dynamic transmission. Yunnan Province and Guangdong Province had the highest imported cases in the 2013 epidemic. In the locations with local dengue transmission, most of imported cases occurred from June to November 2013 while local dengue cases developed from July to December, 2013. There were significant variations for the incidences of dengue, in terms of age distributions, among different geographic locations. However, gender differences were identified in Guangzhou, Foshan and Xishuangbanna. DENV 1–3 were detected in all locations with the disease outbreaks. Some genotypes were detected in more than one locations and more than one genotypes have been detected in several locations. The dengue viruses introduced to outbreak areas were predominantly from Southeast Asia. In Guangdong Province, the phylogeographical results indicated that dengue viruses of DENV 1 were transmitted to neighboring cities Foshan and Zhongshan from Guangzhou city, and then transmitted to Jiangmen city. The virus in DENV 3 was introduced to Guangzhou city, Guangdong Province from Xishuangbanna prefecture, Yunnan Province.

Conclusions

Repeated dengue virus introductions from Southeast Asia and subsequent domestic dengue transmission within different regions may have contributed to the dengue epidemics in China, 2013.

Dengue is the most prevalent and rapidly spreading mosquito-borne viral disease. As an imported disease in China, the imported cases play a vital role for the local dengue transmission. There were dengue outbreaks in three Provinces (covering nine Cities/Prefectures) of China in 2013, with several regions had their first dengue outbreak in history including the one from central China. There has been no study so far to explore the dengue transmission dynamics between different regions in China. The purpose of the study is to describe the 2013 dengue epidemiological characteristics and to explore the transmission dynamics of dengue viruses between epidemic focus. The study results indicated that repeated dengue virus introductions from Southeast Asia and subsequent domestic dengue transmission within different regions may have contributed to the dengue epidemics in China, 2013. Population movement could have played a critical role in dengue dynamic transmission, which introduced dengue viruses to non-epidemic areas at broad or finer spatial scales. Therefore, it should be considered in the design of mosquito eradication campaign for dengue control and prevention.

The interplay of vaccination and vector control on small dengue networks

Dengue fever is a major public health issue affecting billions of people in over 100 countries across the globe. This challenge is growing as the invasive mosquito vectors, Aedes aegypti and Aedes albopictus, expand their distributions and increase their population sizes. Hence there is an increasing need to devise effective control methods that can contain dengue outbreaks. Here we construct an epidemiological model for virus transmission between vectors and hosts on a network of host populations distributed among city and town patches, and investigate disease control through vaccination and vector control using variants of the sterile insect technique (SIT). Analysis of the basic reproductive number and simulations indicate that host movement across this small network influences the severity of epidemics. Both vaccination and vector control strategies are investigated as methods of disease containment and our results indicate that these controls can be made more effective with mixed strategy solutions. We predict that reduced lethality through poor SIT methods or imperfectly efficacious vaccines will impact efforts to control disease spread. In particular, weakly efficacious vaccination strategies against multiple virus serotype diversity may be counter productive to disease control efforts. Even so, failings of one method may be mitigated by supplementing it with an alternative control strategy. Generally, our network approach encourages decision making to consider connected populations, to emphasise that successful control methods must effectively suppress dengue epidemics at this landscape scale.

Spatial Effects on the Multiplicity of Plasmodium falciparum Infections

As malaria is being pushed back on many frontiers and global case numbers are declining, accurate measurement and prediction of transmission becomes increasingly difficult. Low transmission settings are characterised by high levels of spatial heterogeneity, which stands in stark contrast to the widely used assumption of spatially homogeneous transmission used in mathematical transmission models for malaria. In the present study an individual-based mathematical malaria transmission model that incorporates multiple parasite clones, variable human exposure and duration of infection, limited mosquito flight distance and most importantly geographically heterogeneous human and mosquito population densities was used to illustrate the differences between homogeneous and heterogeneous transmission assumptions when aiming to predict surrogate indicators of transmission intensity such as population parasite prevalence or multiplicity of infection (MOI). In traditionally highly malaria endemic regions where most of the population harbours malaria parasites, humans are often infected with multiple parasite clones. However, studies have shown also in areas with low overall parasite prevalence, infection with multiple parasite clones is a common occurrence. Mathematical models assuming homogeneous transmission between humans and mosquitoes cannot explain these observations. Heterogeneity of transmission can arise from many factors including acquired immunity, body size and occupational exposure. In this study, we show that spatial heterogeneity has a profound effect on predictions of MOI and parasite prevalence. We illustrate, that models assuming homogeneous transmission underestimate average MOI in low transmission settings when compared to field data and that spatially heterogeneous models predict stable transmission at much lower overall parasite prevalence. Therefore it is very important that models used to guide malaria surveillance and control strategies in low transmission and elimination settings take into account the spatial features of the specific target area, including human and mosquito vector distribution.

Day-to-Day Population Movement and the Management of Dengue Epidemics

Dengue is a growing public health problem in tropical and subtropical cities. It is transmitted by mosquitoes, and the main strategy for epidemic prevention and control is insecticide fumigation. Effective management is, however, proving elusive. People’s day-to-day movement about the city is believed to be an important factor in the epidemiological dynamics. We use a simple model to examine the fundamental roles of broad demographic and spatial structures in epidemic initiation, growth and control. We show that the key factors are local dilution, characterised by the vector–host ratio, and spatial connectivity, characterised by the extent of habitually variable movement patterns. Epidemic risk in the population is driven by the demographic groups that frequent the areas with the highest vector–host ratio, even if they only spend some of their time there. Synchronisation of epidemic trajectories in different demographic groups is governed by the vector–host ratios to which they are exposed and the strength of connectivity. Strategies for epidemic prevention and management may be made more effective if they take into account the fluctuating landscape of transmission intensity associated with spatial heterogeneity in the vector–host ratio and people’s day-to-day movement patterns.

Use of Household Cluster Investigations to Identify Factors Associated with Chikungunya Virus Infection and Frequency of Case Reporting in Puerto Rico

BACKGROUND

Chikungunya virus (CHIKV) is transmitted by Aedes species mosquitoes and is the cause of an acute febrile illness characterized by potentially debilitating arthralgia. After emerging in the Caribbean in late 2013, the first locally-acquired case reported to public health authorities in Puerto Rico occurred in May 2014. During June-August 2014, household-based cluster investigations were conducted to identify factors associated with infection, development of disease, and case reporting.

METHODOLOGY/PRINCIPAL FINDINGS

Residents of households within a 50-meter radius of the residence of laboratory-positive chikungunya cases that had been reported to Puerto Rico Department of Health (PRDH) were offered participation in the investigation. Participants provided a serum specimen and answered a questionnaire that collected information on demographic factors, household characteristics, recent illnesses, healthcare seeking behaviors, and clinical diagnoses. Current CHIKV infection was identified by rRT-PCR, and recent CHIKV infection was defined by detection of either anti-CHIKV IgM or IgG antibody. Among 250 participants, 74 (30%) had evidence of CHIKV infection, including 12 (5%) with current and 62 (25%) with recent CHIKV infection. All specimens from patients with CHIKV infection that were collected within four days, two weeks, and three weeks of illness onset were positive by RT-PCR, IgM ELISA, and IgG ELISA, respectively. Reporting an acute illness in the prior three months was strongly associated with CHIKV infection (adjusted odds ratio [aOR] = 21.6, 95% confidence interval [CI]: 9.24-50.3). Use of air conditioning (aOR = 0.50, 95% CI = 0.3-0.9) and citronella candles (aOR = 0.4, 95% CI = 0.1-0.9) were associated with protection from CHIKV infection. Multivariable analysis indicated that arthralgia (aOR = 51.8, 95% CI = 3.8-700.8) and skin rash (aOR = 14.2, 95% CI = 2.4-84.7) were strongly associated with CHIKV infection. Hierarchical cluster analysis of signs and symptoms reported by CHIKV-infected participants demonstrated that fever, arthralgia, myalgia, headache, and chills tended to occur simultaneously. Rate of symptomatic CHIKV infection (defined by arthralgia with fever or skin rash) was 62.5%. Excluding index case-patients, 22 (63%) participants with symptomatic CHIKV infection sought medical care, of which 5 (23%) were diagnosed with chikungunya and 2 (9%) were reported to PRDH.

CONCLUSIONS/SIGNIFICANCE

This investigation revealed high rates of CHIKV infection among household members and neighbors of chikungunya patients, and that behavioral interventions such as use of air conditioning were associated with prevention of CHIKV infection. Nearly two-thirds of patients with symptomatic CHIKV infection sought medical care, of which less than one-quarter were reportedly diagnosed with chikungunya and one-in-ten were reported to public health authorities. These findings emphasize the need for point-of-care rapid diagnostic tests to optimize identification and reporting of chikungunya patients.

Climate forcing and infectious disease transmission in urban landscapes: integrating demographic and socioeconomic heterogeneity

Urbanization and climate change are the two major environmental challenges of the 21st century. The dramatic expansion of cities around the world creates new conditions for the spread, surveillance, and control of infectious diseases. In particular, urban growth generates pronounced spatial heterogeneity within cities, which can modulate the effect of climate factors at local spatial scales in large urban environments. Importantly, the interaction between environmental forcing and socioeconomic heterogeneity at local scales remains an open area in infectious disease dynamics, especially for urban landscapes of the developing world. A quantitative and conceptual framework on urban health with a focus on infectious diseases would benefit from integrating aspects of climate forcing, population density, and level of wealth. In this paper, we review what is known about these drivers acting independently and jointly on urban infectious diseases; we then outline elements that are missing and would contribute to building such a framework.

DengueME: A Tool for the Modeling and Simulation of Dengue Spatiotemporal Dynamics

The prevention and control of dengue are great public health challenges for many countries, particularly since 2015, as other arboviruses have been observed to interact significantly with dengue virus. Different approaches and methodologies have been proposed and discussed by the research community. An important tool widely used is modeling and simulation, which help us to understand epidemic dynamics and create scenarios to support planning and decision making processes. With this aim, we proposed and developed DengueME, a collaborative open source platform to simulate dengue disease and its vector's dynamics. It supports compartmental and individual-based models, implemented over a GIS database, that represent Aedes aegypti population dynamics, human demography, human mobility, urban landscape and dengue transmission mediated by human and mosquito encounters. A user-friendly graphical interface was developed to facilitate model configuration and data input, and a library of models was developed to support teaching-learning activities. DengueME was applied in study cases and evaluated by specialists. Other improvements will be made in future work, to enhance its extensibility and usability.

The Importance of Socio-Economic Versus Environmental Risk Factors for Reported Dengue Cases in Java, Indonesia

BACKGROUND

Dengue is a major mosquito-borne viral disease and an important public health problem. Identifying which factors are important determinants in the risk of dengue infection is critical in supporting and guiding preventive measures. In South-East Asia, half of all reported fatal infections are recorded in Indonesia, yet little is known about the epidemiology of dengue in this country.

METHODOLOGY/PRINCIPAL FINDINGS

Hospital-reported dengue cases in Banyumas regency, Central Java were examined to build Bayesian spatial and spatio-temporal models assessing the influence of climatic, demographic and socio-economic factors on the risk of dengue infection. A socio-economic factor linking employment type and economic status was the most influential on the risk of dengue infection in the Regency. Other factors such as access to healthcare facilities and night-time temperature were also found to be associated with higher risk of reported dengue infection but had limited explanatory power.

CONCLUSIONS/SIGNIFICANCE

Our data suggest that dengue infections are triggered by indoor transmission events linked to socio-economic factors (employment type, economic status). Preventive measures in this area should therefore target also specific environments such as schools and work areas to attempt and reduce dengue burden in this community. Although our analysis did not account for factors such as variations in immunity which need further investigation, this study can advise preventive measures in areas with similar patterns of reported dengue cases and environment.

Dengue Sentinel Traveler Surveillance: Monthly and Yearly Notification Trends among Japanese Travelers, 2006-2014

Background

Dengue is becoming an increasing threat to non-endemic countries. In Japan, the reported number of imported cases has been rising, and the first domestic dengue outbreak in nearly 70 years was confirmed in 2014, highlighting the need for greater situational awareness and better-informed risk assessment.

Methods

Using national disease surveillance data and publically available traveler statistics, we compared monthly and yearly trends in the destination country-specific dengue notification rate per 100,000 Japanese travelers with those of domestic dengue cases in the respective country visited during 2006–2014. Comparisons were made for countries accounting for the majority of importations; yearly comparisons were restricted to countries where respective national surveillance data were publicly available.

Results

There were 1007 imported Japanese dengue cases (Bali, Indonesia (n = 202), the Philippines (n = 230), Thailand (n = 160), and India (n = 152)). Consistent with historic local dengue seasonality, monthly notification rate among travelers peaked in August in Thailand, September in the Philippines, and in Bali during April with a smaller peak in August. While the number of travelers to Bali was greatest in August, the notification rate was highest in April. Annually, trends in the notification rate among travelers to the Philippines and Thailand also closely reflected local notification trends.

Conclusion

Travelers to dengue-endemic countries appear to serve as reliable “sentinels”, with the trends in estimated risk of dengue infection among Japanese travelers closely reflecting local dengue trends, both seasonally and annually. Sentinel traveler surveillance can contribute to evidence-based pretravel advice, and help inform risk assessments and decision-making for importation and potentially for subsequent secondary transmission. As our approach takes advantage of traveler data that are readily available as a proxy denominator, sentinel traveler surveillance can be a practical surveillance tool that other countries could consider for implementation.

With increasing globalization, the threat of dengue is rising in areas that were previously unaffected. Japan has been experiencing a rise in notifications of imported cases, and in 2014 confirmed the first domestic outbreak in nearly 70 years. Such events prompted the country to more actively utilize existing imported dengue case data among travelers to inform situational awareness, risk assessment, and evidence-based decision-making. Using both national disease surveillance data and publically available traveler statistics, we compared monthly and yearly trends between reported numbers of dengue cases among Japanese travelers and those of domestic dengue cases in the countries visited. By using the number of Japanese travelers to a dengue-endemic country as an approximate denominator, we estimated the risk of dengue infection among travelers to the country. This method is more appropriate than simply monitoring the number of reported imported cases because it accounts for fluctuating numbers of travelers, such as during vacation periods. This study demonstrated that the trends in dengue notifications among travelers were consistent with local dengue trends, both yearly and seasonally. Our simple approach, which takes advantage of existing data, may be readily adopted elsewhere to help inform risk of importation and potential subsequent domestic transmission.

Modeling Mosquito-Borne Disease Spread in U.S. Urbanized Areas: The Case of Dengue in Miami

Expansion of mosquito-borne pathogens into more temperate regions of the world necessitates tools such as mathematical models for understanding the factors that contribute to the introduction and emergence of a disease in populations naïve to the disease. Often, these models are not developed and analyzed until after a pathogen is detected in a population. In this study, we develop a spatially explicit stochastic model parameterized with publicly available U.S. Census data for studying the potential for disease spread in Urbanized Areas of the United States. To illustrate the utility of the model, we specifically study the potential for introductions of dengue to lead to autochthonous transmission and outbreaks in a population representative of the Miami Urbanized Area, where introductions of dengue have occurred frequently in recent years. We describe seasonal fluctuations in mosquito populations by fitting a population model to trap data provided by the Miami-Dade Mosquito Control Division. We show that the timing and location of introduced cases could play an important role in determining both the probability that local transmission occurs as well as the total number of cases throughout the entire region following introduction. We show that at low rates of clinical presentation, small outbreaks of dengue could go completely undetected during a season, which may confound mitigation efforts that rely upon detection. We discuss the sensitivity of the model to several critical parameter values that are currently poorly characterized and motivate the collection of additional data to strengthen the predictive power of this and similar models. Finally, we emphasize the utility of the general structure of this model in studying mosquito-borne diseases such as chikungunya and Zika virus in other regions.

Big city, small world: density, contact rates, and transmission of dengue across Pakistan

Macroscopic descriptions of populations commonly assume that encounters between individuals are well mixed; i.e. each individual has an equal chance of coming into contact with any other individual. Relaxing this assumption can be challenging though, due to the difficulty of acquiring detailed knowledge about the non-random nature of encounters. Here, we fitted a mathematical model of dengue virus transmission to spatial time-series data from Pakistan and compared maximum-likelihood estimates of 'mixing parameters' when disaggregating data across an urban-rural gradient. We show that dynamics across this gradient are subject not only to differing transmission intensities but also to differing strengths of nonlinearity due to differences in mixing. Accounting for differences in mobility by incorporating two fine-scale, density-dependent covariate layers eliminates differences in mixing but results in a doubling of the estimated transmission potential of the large urban district of Lahore. We furthermore show that neglecting spatial variation in mixing can lead to substantial underestimates of the level of effort needed to control a pathogen with vaccines or other interventions. We complement this analysis with estimates of the relationships between dengue transmission intensity and other putative environmental drivers thereof.

Experiences with insecticide-treated curtains: a qualitative study in Iquitos, Peru

BACKGROUND

Dengue is an arthropod-borne viral disease responsible for approximately 400 million infections annually; the only available method of prevention is vector control. It has been previously demonstrated that insecticide treated curtains (ITCs) can lower dengue vector infestations in and around houses. As part of a larger trial examining whether ITCs could reduce dengue transmission in Iquitos, Peru, the objective of this study was to characterize the participants' experience with the ITCs using qualitative methods.

METHODS

Knowledge, attitudes, and practices (KAP) surveys (at baseline, and 9 and 27 months post-ITC distribution, with n = 593, 595 and 511, respectively), focus group discussions (at 6 and 12 months post-ITC distribution, with n = 18 and 33, respectively), and 11 one-on-one interviews (at 12 months post-distribution) were conducted with 605 participants who received ITCs as part of a cluster-randomized trial.

RESULTS

Focus groups at 6 months post-ITC distribution revealed that individuals had observed their ITCs to function for approximately 3 months, after which they reported the ITCs were no longer working. Follow up revealed that the ITCs required re-treatment with insecticide at approximately 1 year post-distribution. Over half (55.3 %, n = 329) of participants at 9 months post-ITC distribution and over a third (34.8 %, n = 177) at 27 months post-ITC distribution reported perceiving a decrease in the number of mosquitoes in their home. The percentage of participants who would recommend ITCs to their family or friends in the future remained high throughout the study (94.3 %, n = 561 at 9 months and 94.6 %, n = 488 at 27 months post-distribution). When asked why, participants reported that ITCs were effective at reducing mosquitoes (81.6 and 37.8 %, at 9 and 27 months respectively), that they prevent dengue (5.7 and 51.2 %, at 9 and 27 months), that they are "beautiful" (5.9 and 3.1 %), as well as other reasons (6.9 and 2.5 %).

CONCLUSION

ITCs have substantial potential for long term dengue vector control because they are liked by users, both for their perceived effectiveness and for aesthetic reasons, and because they require little proactive behavioral effort on the part of the users. Our results highlight the importance of gathering process (as opposed to outcome) data during vector control studies, without which researchers would not have become aware that the ITCs had lost effectiveness early in the trial.

A modified theoretical framework to assess implementation fidelity of adaptive public health interventions

BACKGROUND

One of the major debates in implementation research turns around fidelity and adaptation. Fidelity is the degree to which an intervention is implemented as intended by its developers. It is meant to ensure that the intervention maintains its intended effects. Adaptation is the process of implementers or users bringing changes to the original design of an intervention. Depending on the nature of the modifications brought, adaptation could either be potentially positive or could carry the risk of threatening the theoretical basis of the intervention, resulting in a negative effect on expected outcomes. Adaptive interventions are those for which adaptation is allowed or even encouraged. Classical fidelity dimensions and conceptual frameworks do not address the issue of how to adapt an intervention while still maintaining its effectiveness.

DISCUSSION

We support the idea that fidelity and adaptation co-exist and that adaptations can impact either positively or negatively on the intervention's effectiveness. For adaptive interventions, research should answer the question how an adequate fidelity-adaptation balance can be reached. One way to address this issue is by looking systematically at the aspects of an intervention that are being adapted. We conducted fidelity research on the implementation of an empowerment strategy for dengue prevention in Cuba. In view of the adaptive nature of the strategy, we anticipated that the classical fidelity dimensions would be of limited use for assessing adaptations. The typology we used in the assessment-implemented, not-implemented, modified, or added components of the strategy-also had limitations. It did not allow us to answer the question which of the modifications introduced in the strategy contributed to or distracted from outcomes. We confronted our empirical research with existing literature on fidelity, and as a result, considered that the framework for implementation fidelity proposed by Carroll et al. in 2007 could potentially meet our concerns. We propose modifications to the framework to assess both fidelity and adaptation. The modified Carroll et al.'s framework we propose may permit a comprehensive assessment of the implementation fidelity-adaptation balance required when implementing adaptive interventions, but more empirical research is needed to validate it.

Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America

BACKGROUND

Worldwide, dengue is an unrelenting economic and health burden. Dengue outbreaks have become increasingly common, which place great strain on health infrastructure and services. Early warning models could allow health systems and vector control programmes to respond more cost-effectively and efficiently.

METHODOLOGY/PRINCIPAL FINDINGS

The Shewhart method and Endemic Channel were used to identify alarm variables that may predict dengue outbreaks. Five country datasets were compiled by epidemiological week over the years 2007-2013. These data were split between the years 2007-2011 (historic period) and 2012-2013 (evaluation period). Associations between alarm/ outbreak variables were analysed using logistic regression during the historic period while alarm and outbreak signals were captured during the evaluation period. These signals were combined to form alarm/ outbreak periods, where 2 signals were equal to 1 period. Alarm periods were quantified and used to predict subsequent outbreak periods. Across Mexico and Dominican Republic, an increase in probable cases predicted outbreaks of hospitalised cases with sensitivities and positive predictive values (PPV) of 93%/ 83% and 97%/ 86% respectively, at a lag of 1-12 weeks. An increase in mean temperature ably predicted outbreaks of hospitalised cases in Mexico and Brazil, with sensitivities and PPVs of 79%/ 73% and 81%/ 46% respectively, also at a lag of 1-12 weeks. Mean age was predictive of hospitalised cases at sensitivities and PPVs of 72%/ 74% and 96%/ 45% in Mexico and Malaysia respectively, at a lag of 4-16 weeks.

CONCLUSIONS/SIGNIFICANCE

An increase in probable cases was predictive of outbreaks, while meteorological variables, particularly mean temperature, demonstrated predictive potential in some countries, but not all. While it is difficult to define uniform variables applicable in every country context, the use of probable cases and meteorological variables in tailored early warning systems could be used to highlight the occurrence of dengue outbreaks or indicate increased risk of dengue transmission.

Spatial spread of dengue in a non-endemic tropical city in northern Argentina

After more than eighty years dengue reemerged in Argentina in 1997. Since then, the largest epidemic in terms of geographical extent, magnitude and mortality, was recorded in 2009. In this report we analyzed the DEN-1 epidemic spread in Orán, a mid-size city in a non-endemic tropical area in Northern Argentina, and its correlation with demographic and socioeconomic factors. Cases were diagnosed by ELISA between January and June 2009. We applied a space-time and spatial scan statistic under a Poisson model. Possible association between dengue incidence and socio-economic variables was studied with the Spearman correlation test. The epidemic started from an imported case from Bolivia and space-time analysis detected two clusters: one on February and other in April (in the south and the northeast of the city respectively) with risk ratios of 25.24 and 4.07 (p<0.01). Subsequent cases spread widely around the city without significant space-temporal clustering. Maximum values of the entomological indices were observed in January, at the beginning of the epidemic (B=21.96; LH=8.39). No statistically significant association between socioeconomic variables and dengue incidence was found but positive correlation between population size and the number of cases (p<0.05) was detected. Two mechanisms may explain the observed pattern of epidemic spread in this non-endemic tropical city: a) Short range dispersal of mosquitoes and people generates clusters of cases and b) long-distance (within the city) human movement contributes to a quasi-random distribution of cases.

Projected Impact of Dengue Vaccination in Yucatán, Mexico

Dengue vaccines will soon provide a new tool for reducing dengue disease, but the effectiveness of widespread vaccination campaigns has not yet been determined. We developed an agent-based dengue model representing movement of and transmission dynamics among people and mosquitoes in Yucatán, Mexico, and simulated various vaccine scenarios to evaluate effectiveness under those conditions. This model includes detailed spatial representation of the Yucatán population, including the location and movement of 1.8 million people between 375,000 households and 100,000 workplaces and schools. Where possible, we designed the model to use data sources with international coverage, to simplify re-parameterization for other regions. The simulation and analysis integrate 35 years of mild and severe case data (including dengue serotype when available), results of a seroprevalence survey, satellite imagery, and climatological, census, and economic data. To fit model parameters that are not directly informed by available data, such as disease reporting rates and dengue transmission parameters, we developed a parameter estimation toolkit called AbcSmc, which we have made publicly available. After fitting the simulation model to dengue case data, we forecasted transmission and assessed the relative effectiveness of several vaccination strategies over a 20 year period. Vaccine efficacy is based on phase III trial results for the Sanofi-Pasteur vaccine, Dengvaxia. We consider routine vaccination of 2, 9, or 16 year-olds, with and without a one-time catch-up campaign to age 30. Because the durability of Dengvaxia is not yet established, we consider hypothetical vaccines that confer either durable or waning immunity, and we evaluate the use of booster doses to counter waning. We find that plausible vaccination scenarios with a durable vaccine reduce annual dengue incidence by as much as 80% within five years. However, if vaccine efficacy wanes after administration, we find that there can be years with larger epidemics than would occur without any vaccination, and that vaccine booster doses are necessary to prevent this outcome.

Dengue is a mosquito-transmitted viral disease that is common throughout the tropics. Despite a long history in humans and extensive efforts to control dengue transmission in many countries, the number, severity, and geographic range of reported cases is increasing. Most control efforts have focused on controlling mosquito populations, but the main vector, Aedes aegypti, flourishes in human-disturbed and indoor environments. Because the mosquitoes prefer to bite during the day when people are active and potentially moving around high-risk locations, fixed barriers like bed nets are not effective. Several dengue vaccines are being actively developed and may become valuable tools in dengue control. Using historical dengue data from Yucatán, Mexico, we fit a detailed simulation of human and mosquito populations to project future transmission, then used efficacy data from vaccine trials to evaluate the benefit of potential vaccination deployment strategies in the region. For a durable vaccine, we find that population-level, annual vaccine effectiveness approaches 65% by the end of the 20-year forecast period. For waning vaccines, however, effectiveness is greatly reduced–and sometimes negative–unless booster vaccinations are used.

Reduced Incidence of Chikungunya Virus Infection in Communities with Ongoing Aedes Aegypti Mosquito Trap Intervention Studies - Salinas and Guayama, Puerto Rico, November 2015-February 2016

Aedes species mosquitoes transmit chikungunya virus, as well as dengue and Zika viruses, and bite most often during the day.* Infectious mosquito bites frequently occur in and around homes (1,2). Caribbean countries first reported local transmission of chikungunya virus in December 2013, and soon after, chikungunya virus spread throughout the Americas (3). Puerto Rico reported its first laboratory-positive chikungunya case in May 2014 (4), and subsequently identified approximately 29,000 suspected cases throughout the island by the end of 2015.(†) Because conventional vector control approaches often fail to result in effective and sustainable prevention of infection with viruses transmitted by Aedes mosquitoes (5), and to improve surveillance of mosquito population densities, CDC developed an Autocidal Gravid Ovitrap (AGO) (6) to attract and capture the female Aedes aegypti mosquitoes responsible for transmission of infectious agents to humans (Figure). The AGO trap is a simple, low-cost device that requires no use of pesticides and no servicing for an extended period of time (6).

Mapping global environmental suitability for Zika virus

Zika virus was discovered in Uganda in 1947 and is transmitted by Aedes mosquitoes, which also act as vectors for dengue and chikungunya viruses throughout much of the tropical world. In 2007, an outbreak in the Federated States of Micronesia sparked public health concern. In 2013, the virus began to spread across other parts of Oceania and in 2015, a large outbreak in Latin America began in Brazil. Possible associations with microcephaly and Guillain-Barré syndrome observed in this outbreak have raised concerns about continued global spread of Zika virus, prompting its declaration as a Public Health Emergency of International Concern by the World Health Organization. We conducted species distribution modelling to map environmental suitability for Zika. We show a large portion of tropical and sub-tropical regions globally have suitable environmental conditions with over 2.17 billion people inhabiting these areas.

DOI:http://dx.doi.org/10.7554/eLife.15272.001

Zika virus is transmitted between humans by mosquitoes. The majority of infections cause mild flu-like symptoms, but neurological complications in adults and infants have been found in recent outbreaks.

Although it was discovered in Uganda in 1947, Zika only caused sporadic infections in humans until 2007, when it caused a large outbreak in the Federated States of Micronesia. The virus later spread across Oceania, was first reported in Brazil in 2015 and has since rapidly spread across Latin America. This has led many people to question how far it will continue to spread. There was therefore a need to define the areas where the virus could be transmitted, including the human populations that might be risk in these areas.

Messina et al. have now mapped the areas that provide conditions that are highly suitable for the spread of the Zika virus. These areas occur in many tropical and sub-tropical regions around the globe. The largest areas of risk in the Americas lie in Brazil, Colombia and Venezuela. Although Zika has yet to be reported in the USA, a large portion of the southeast region from Texas through to Florida is highly suitable for transmission. Much of sub-Saharan Africa (where several sporadic cases have been reported since the 1950s) also presents an environment that is highly suitable for the Zika virus. While no cases have yet been reported in India, a large portion of the subcontinent is also suitable for Zika transmission.

Over 2 billion people live in Zika-suitable areas globally, and in the Americas alone, over 5.4 million births occurred in 2015 within such areas. It is important, however, to recognize that not all individuals living in suitable areas will necessarily be exposed to Zika.

We still lack a great deal of basic epidemiological information about Zika. More needs to be known about the species of mosquito that spreads the disease and how the Zika virus interacts with related viruses such as dengue. As such information becomes available and clinical cases become routinely diagnosed, the global evidence base will be strengthened, which will improve the accuracy of future maps.

DOI:http://dx.doi.org/10.7554/eLife.15272.002

Dengue and chikungunya: modelling the expansion of mosquito-borne viruses into naïve populations

With the recent global spread of a number of mosquito-borne viruses, there is an urgent need to understand the factors that contribute to the ability of viruses to expand into naïve populations. Using dengue and chikungunya viruses as case studies, we detail the necessary components of the expansion process: presence of the mosquito vector; introduction of the virus; and suitable conditions for local transmission. For each component we review the existing modelling approaches that have been used to understand recent emergence events or to assess the risk of future expansions. We identify gaps in our knowledge that are related to each of the distinct aspects of the human-mosquito transmission cycle: mosquito ecology; human-mosquito contact; mosquito-virus interactions; and human-virus interactions. Bridging these gaps poses challenges to both modellers and empiricists, but only through further integration of models and data will we improve our ability to better understand, and ultimately control, several infectious diseases that exert a significant burden on human health.

Factors Associated with Correct and Consistent Insecticide Treated Curtain Use in Iquitos, Peru

Dengue is an arthropod-borne virus of great public health importance, and control of its mosquito vectors is currently the only available method for prevention. Previous research has suggested that insecticide treated curtains (ITCs) can lower dengue vector infestations in houses. This observational study investigated individual and household-level socio-demographic factors associated with correct and consistent use of ITCs in Iquitos, Peru. A baseline knowledge, attitudes, and practices (KAP) survey was administered to 1,333 study participants, and ITCs were then distributed to 593 households as part of a cluster-randomized trial. Follow up KAP surveys and ITC-monitoring checklists were conducted at 9, 18, and 27 months post-ITC distribution. At 9 months post-distribution, almost 70% of ITCs were hanging properly (e.g. hanging fully extended or tied up), particularly those hung on walls compared to other locations. Proper ITC hanging dropped at 18 months to 45.7%. The odds of hanging ITCs correctly and consistently were significantly greater among those participants who were housewives, knew three or more correct symptoms of dengue and at least one correct treatment for dengue, knew a relative or close friend who had had dengue, had children sleeping under a mosquito net, or perceived a change in the amount of mosquitoes in the home. Additionally, the odds of recommending ITCs in the future were significantly greater among those who perceived a change in the amount of mosquitoes in the home (e.g. perceived the ITCs to be effective). Despite various challenges associated with the sustained effectiveness of the selected ITCs, almost half of the ITCs were still hanging at 18 months, suggesting a feasible vector control strategy for sustained community use.

Dengue is an arthropod-borne virus of great public health importance. Vector control is currently the only available method for dengue prevention. This cluster-randomized trial investigated individual and household-level socio-demographic factors associated with correct and consistent use of insecticide-treated curtains (ITCs)—one promising vector control method—in Iquitos, Peru. Most people preferred to hang the ITCs in doorways and as room dividers, but also hung them as curtains on windows and on their walls. We assessed who still had their ITCs hanging or tied up at 9 months and 18 months after distribution, and found that use of the ITCs decreased over time to about half. When we explored who was more likely to be using the ITCs correctly (having them hanging in place, or tied up in place, or washed without bleach and avoiding direct sunlight), we found that those who knew more about dengue, knew someone who had dengue, had young children in their homes sleeping under an insecticide treated mosquito net, or who perceived the ITCs to work well, were more likely to be using their ITCs than others. Despite various challenges in sustained ITC effectiveness in this study, the fact that almost half of the homes still had the ITCs hanging at 18 months suggests this vector control strategy is feasible for long term community use.

Is Dengue Vector Control Deficient in Effectiveness or Evidence?: Systematic Review and Meta-analysis

BACKGROUND

Although a vaccine could be available as early as 2016, vector control remains the primary approach used to prevent dengue, the most common and widespread arbovirus of humans worldwide. We reviewed the evidence for effectiveness of vector control methods in reducing its transmission.

METHODOLOGY/PRINCIPAL FINDINGS

Studies of any design published since 1980 were included if they evaluated method(s) targeting Aedes aegypti or Ae. albopictus for at least 3 months. Primary outcome was dengue incidence. Following Cochrane and PRISMA Group guidelines, database searches yielded 960 reports, and 41 were eligible for inclusion, with 19 providing data for meta-analysis. Study duration ranged from 5 months to 10 years. Studies evaluating multiple tools/approaches (23 records) were more common than single methods, while environmental management was the most common method (19 studies). Only 9/41 reports were randomized controlled trials (RCTs). Two out of 19 studies evaluating dengue incidence were RCTs, and neither reported any statistically significant impact. No RCTs evaluated effectiveness of insecticide space-spraying (fogging) against dengue. Based on meta-analyses, house screening significantly reduced dengue risk, OR 0.22 (95% CI 0.05-0.93, p = 0.04), as did combining community-based environmental management and water container covers, OR 0.22 (95% CI 0.15-0.32, p<0.0001). Indoor residual spraying (IRS) did not impact significantly on infection risk (OR 0.67; 95% CI 0.22-2.11; p = 0.50). Skin repellents, insecticide-treated bed nets or traps had no effect (p>0.5), but insecticide aerosols (OR 2.03; 95% CI 1.44-2.86) and mosquito coils (OR 1.44; 95% CI 1.09-1.91) were associated with higher dengue risk (p = 0.01). Although 23/41 studies examined the impact of insecticide-based tools, only 9 evaluated the insecticide susceptibility status of the target vector population during the study.

CONCLUSIONS/SIGNIFICANCE

This review and meta-analysis demonstrate the remarkable paucity of reliable evidence for the effectiveness of any dengue vector control method. Standardised studies of higher quality to evaluate and compare methods must be prioritised to optimise cost-effective dengue prevention.

Underrecognition of Dengue during 2013 Epidemic in Luanda, Angola

Case detection should be improved by instituting routine laboratory-based surveillance for acute febrile illnesses in Africa.

Dengue in Angola

During the 2013 dengue epidemic in Luanda, Angola, 811 dengue rapid diagnostic test–positive cases were reported to the Ministry of Health. To better understand the magnitude of the epidemic and identify risk factors for dengue virus (DENV) infection, we conducted cluster surveys around households of case-patients and randomly selected households 6 weeks after the peak of the epidemic. Of 173 case cluster participants, 16 (9%) exhibited evidence of recent DENV infection. Of 247 random cluster participants, 25 (10%) had evidence of recent DENV infection. Of 13 recently infected participants who had a recent febrile illness, 7 (54%) had sought medical care, and 1 (14%) was hospitalized with symptoms consistent with severe dengue; however, none received a diagnosis of dengue. Behavior associated with protection from DENV infection included recent use of mosquito repellent or a bed net. These findings suggest that the 2013 dengue epidemic was larger than indicated by passive surveillance data.

Developing a Time Series Predictive Model for Dengue in Zhongshan, China Based on Weather and Guangzhou Dengue Surveillance Data

Background

Dengue is a re-emerging infectious disease of humans, rapidly growing from endemic areas to dengue-free regions due to favorable conditions. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. This study aims to examine the impact of dengue epidemics in Guangzhou, China, and to develop a predictive model for Zhongshan based on local weather conditions and Guangzhou dengue surveillance information.

Methods

We obtained weekly dengue case data from 1^st January, 2005 to 31^st December, 2014 for Guangzhou and Zhongshan city from the Chinese National Disease Surveillance Reporting System. Meteorological data was collected from the Zhongshan Weather Bureau and demographic data was collected from the Zhongshan Statistical Bureau. A negative binomial regression model with a log link function was used to analyze the relationship between weekly dengue cases in Guangzhou and Zhongshan, controlling for meteorological factors. Cross-correlation functions were applied to identify the time lags of the effect of each weather factor on weekly dengue cases. Models were validated using receiver operating characteristic (ROC) curves and k-fold cross-validation.

Results

Our results showed that weekly dengue cases in Zhongshan were significantly associated with dengue cases in Guangzhou after the treatment of a 5 weeks prior moving average (Relative Risk (RR) = 2.016, 95% Confidence Interval (CI): 1.845–2.203), controlling for weather factors including minimum temperature, relative humidity, and rainfall. ROC curve analysis indicated our forecasting model performed well at different prediction thresholds, with 0.969 area under the receiver operating characteristic curve (AUC) for a threshold of 3 cases per week, 0.957 AUC for a threshold of 2 cases per week, and 0.938 AUC for a threshold of 1 case per week. Models established during k-fold cross-validation also had considerable AUC (average 0.938–0.967). The sensitivity and specificity obtained from k-fold cross-validation was 78.83% and 92.48% respectively, with a forecasting threshold of 3 cases per week; 91.17% and 91.39%, with a threshold of 2 cases; and 85.16% and 87.25% with a threshold of 1 case. The out-of-sample prediction for the epidemics in 2014 also showed satisfactory performance.

Conclusion

Our study findings suggest that the occurrence of dengue outbreaks in Guangzhou could impact dengue outbreaks in Zhongshan under suitable weather conditions. Future studies should focus on developing integrated early warning systems for dengue transmission including local weather and human movement.

Emerging and re-emerging infectious diseases in an urban city could expand due to increased urbanization, population density, and travel. Dengue, as a mosquito-borne viral disease, has rapidly spread from endemic areas to dengue-free regions, with social, demographic, entomological, and environmental factors affecting its transmission. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. In this study, we demonstrated that the dengue outbreaks in Guangzhou could impact outbreaks in Zhongshan, one of its neighboring cities, if suitable climate conditions are present. Such associations between dengue epidemics in two cities may also suggest the important role human movement has played in the transmission of the disease. Based on the association between dengue epidemics in Guangzhou and Zhongshan, and the association between dengue epidemics and weather conditions, we developed a reliable and robust model that predicts the occurrence of epidemics at diffrent thresholds in Zhongshan. These results could be used by local health departments in developing strategies towards dengue prevention and control, and push the public to pay more attention to social factors like human movement in disease transmission.

Incomplete Protection against Dengue Virus Type 2 Re-infection in Peru

Background

Nearly half of the world’s population is at risk for dengue, yet no licensed vaccine or anti-viral drug is currently available. Dengue is caused by any of four dengue virus serotypes (DENV-1 through DENV-4), and infection by a DENV serotype is assumed to provide life-long protection against re-infection by that serotype. We investigated the validity of this fundamental assumption during a large dengue epidemic caused by DENV-2 in Iquitos, Peru, in 2010–2011, 15 years after the first outbreak of DENV-2 in the region.

Methodology/Principal Findings

We estimated the age-dependent prevalence of serotype-specific DENV antibodies from longitudinal cohort studies conducted between 1993 and 2010. During the 2010–2011 epidemic, active dengue cases were identified through active community- and clinic-based febrile surveillance studies, and acute inapparent DENV infections were identified through contact tracing studies. Based on the age-specific prevalence of DENV-2 neutralizing antibodies, the age distribution of DENV-2 cases was markedly older than expected. Homologous protection was estimated at 35.1% (95% confidence interval: 0%–65.2%). At the individual level, pre-existing DENV-2 antibodies were associated with an incomplete reduction in the frequency of symptoms. Among dengue cases, 43% (26/66) exhibited elevated DENV-2 neutralizing antibody titers for years prior to infection, compared with 76% (13/17) of inapparent infections (age-adjusted odds ratio: 4.2; 95% confidence interval: 1.1–17.7).

Conclusions/Significance

Our data indicate that protection from homologous DENV re-infection may be incomplete in some circumstances, which provides context for the limited vaccine efficacy against DENV-2 in recent trials. Further studies are warranted to confirm this phenomenon and to evaluate the potential role of incomplete homologous protection in DENV transmission dynamics.

Dengue is a mosquito-borne viral illness that imposes a tremendous public health burden on tropical and sub-tropical regions. An estimated 390 million infections occur globally each year, and up to 4 billion people are at risk. Dengue is caused by four dengue virus (DENV) serotypes (DENV-1 to DENV-4). Infection with any DENV can lead to a range of disease outcomes, from mild febrile illness to severe, hemorrhagic manifestations and death. Infection by one serotype has been assume to provide complete and lifelong protection against re-infection by the same serotype, and to our knowledge, instances of re-infection by the same serotype have not been rigorously documented. However, few long-term studies have been conducted in such a way that re-infection by the same serotype could be observed, if it did in fact occur. Our study provides evidence that re-infection may occur in certain circumstances. We draw from data collected during a 2010–2011 DENV-2 epidemic in northeastern Peru, 15 years after the initial DENV-2 outbreak in the region. This finding has significant implications for our understanding of dengue epidemiology and for dengue vaccine formulation, which may need to consider multiple genotypes of each serotype. Data from other long-term dengue epidemiology studies should be analyzed to determine if homologous re-infection is a more widespread phenomenon.

The Risk of Dengue Virus Transmission in Dar es Salaam, Tanzania during an Epidemic Period of 2014

Background

In 2010, 2012, 2013 and 2014 dengue outbreaks have been reported in Dar es Salaam, Tanzania. However, there is no comprehensive data on the risk of transmission of dengue in the country. The objective of this study was to assess the risk of transmission of dengue in Dar es Salaam during the 2014 epidemic.

Methodology/Principal Findings

This cross-sectional study was conducted in Dar es Salaam, Tanzania during the dengue outbreak of 2014. The study involved Ilala, Kinondoni and Temeke districts. Adult mosquitoes were collected using carbon dioxide-propane powered Mosquito Magnet Liberty Plus traps. In each household compound, water-holding containers were examined for mosquito larvae and pupae. Dengue virus infection of mosquitoes was determined using real-time reverse transcription polymerase chain reaction (qRT-PCR). Partial amplification and sequencing of dengue virus genome in infected mosquitoes was performed. A total of 1,000 adult mosquitoes were collected. Over half (59.9%) of the adult mosquitoes were collected in Kinondoni. Aedes aegypti accounted for 17.2% of the mosquitoes of which 90.6% were from Kinondoni. Of a total of 796 houses inspected, 38.3% had water-holding containers in their premises. Kinondoni had the largest proportion of water-holding containers (57.7%), followed by Temeke (31.4%) and Ilala (23.4%). The most common breeding containers for the Aedes mosquitoes were discarded plastic containers and tires. High Aedes infestation indices were observed for all districts and sites, with a house index of 18.1% in Ilala, 25.5% in Temeke and 35.3% in Kinondoni. The respective container indices were 77.4%, 65.2% and 80.2%. Of the reared larvae and pupae, 5,250 adult mosquitoes emerged, of which 61.9% were Ae. aegypti. Overall, 27 (8.18) of the 330 pools of Ae. aegypti were positive for dengue virus. On average, the overall maximum likelihood estimate (MLE) indicates pooled infection rate of 8.49 per 1,000 mosquitoes (95%CI = 5.72–12.16). There was no significant difference in pooled infection rates between the districts. Dengue viruses in the tested mosquitoes clustered into serotype 2 cosmopolitan genotype.

Conclusions/Significance

Ae. aegypti is the main vector of dengue in Dar es Salaam and breeds mainly in medium size plastic containers and tires. The Aedes house indices were high, indicating that the three districts were at high risk of dengue transmission. The 2014 dengue outbreak was caused by Dengue virus serotype 2. The high mosquito larval and pupal indices in the area require intensification of vector surveillance along with source reduction and health education.

Until 2010, little was known about Dengue in Tanzania. Since then, four outbreaks have been reported in Dar es Salaam City. This study was therefore carried out to assess the risk of transmission of dengue in Dar es Salaam during an outbreak in 2014. In this study adult mosquitoes were collected using carbon dioxide-propane powered traps. In addition, household compounds were visited and all water-holding containers examined for presence of mosquito larvae and pupae. Mosquito virus infection was determined using real-time reverse transcription polymerase chain reaction (qRT-PCR). Of the total of 1,000 adult mosquitoes collected, Aedes aegypti accounted for 17.2%. A total of 796 houses were inspected and 38.3% had water-holding containers in their premises. The most common breeding containers for the Aedes mosquitoes were discarded plastic containers and tires. High Aedes infestation indices were observed for all districts and sites, with a house and container indices ranging from 18.1–25.5% and 65.2–80.2%, respectively. The Breteaux indices were 30.6, 20.8 and 25.3 in Ilala, Kinondoni and Temeke, respectively. An overall 8.18% of mosquito pools were infected with dengue virus serotype 2. The overall maximum likelihood estimate of pooled infection rate of 8.49 per 1,000 mosquitoes was observed. This information is useful for the design of appropriate vector surveillance and control strategies in the City of Dar es Salaam.

How Important is Vertical Transmission of Dengue Viruses by Mosquitoes (Diptera: Culicidae)?

Vertical transmission of dengue viruses by mosquitoes was discovered at the end of the late 1970s and has been suggested to be a means by which these viruses persist. However, it is unclear how widespread it is in nature, and its importance in the epidemiology of this disease is still debated. Here, we review the literature on vertical transmission and discuss its role in dengue's epidemiology and control. We conclude that given the number of studies that failed to find evidence of vertical transmission, as well as mathematical models and its mechanistic basis, it is unlikely that vertical transmission is important for the epidemiological persistence of dengue viruses. A combination of asymptomatic infection in humans and movement of people are likely to be more important determinants of dengue's persistence. We argue, however, that there may be some need for further research into the prevalence of dengue viruses in desiccated, as well as diapausing, eggs and the role of horizontal transmission through larval cannibalism.

Human Social Behavior and Demography Drive Patterns of Fine-Scale Dengue Transmission in Endemic Areas of Colombia

Dengue is known to transmit between humans and A. aegypti mosquitoes living in neighboring houses. Although transmission is thought to be highly heterogeneous in both space and time, little is known about the patterns and drivers of transmission in groups of houses in endemic settings. We carried out surveys of PCR positivity in children residing in 2-block patches of highly endemic cities of Colombia. We found high levels of heterogeneity in PCR positivity, varying from less than 30% in 8 of the 10 patches to 56 and 96%, with the latter patch containing 22 children simultaneously PCR positive (PCR22) for DEN2. We then used an agent-based model to assess the likely eco-epidemiological context of this observation. Our model, simulating daily dengue dynamics over a 20 year period in a single two block patch, suggests that the observed heterogeneity most likely derived from variation in the density of susceptible people. Two aspects of human adaptive behavior were critical to determining this density: external social relationships favoring viral introduction (by susceptible residents or infectious visitors) and immigration of households from non-endemic areas. External social relationships generating frequent viral introduction constituted a particularly strong constraint on susceptible densities, thereby limiting the potential for explosive outbreaks and dampening the impact of heightened vectorial capacity. Dengue transmission can be highly explosive locally, even in neighborhoods with significant immunity in the human population. Variation among neighborhoods in the density of local social networks and rural-to-urban migration is likely to produce significant fine-scale heterogeneity in dengue dynamics, constraining or amplifying the impacts of changes in mosquito populations and cross immunity between serotypes.

Socio-economic and Climate Factors Associated with Dengue Fever Spatial Heterogeneity: A Worked Example in New Caledonia

BACKGROUND/OBJECTIVES

Understanding the factors underlying the spatio-temporal distribution of infectious diseases provides useful information regarding their prevention and control. Dengue fever spatio-temporal patterns result from complex interactions between the virus, the host, and the vector. These interactions can be influenced by environmental conditions. Our objectives were to analyse dengue fever spatial distribution over New Caledonia during epidemic years, to identify some of the main underlying factors, and to predict the spatial evolution of dengue fever under changing climatic conditions, at the 2100 horizon.

METHODS

We used principal component analysis and support vector machines to analyse and model the influence of climate and socio-economic variables on the mean spatial distribution of 24,272 dengue cases reported from 1995 to 2012 in thirty-three communes of New Caledonia. We then modelled and estimated the future evolution of dengue incidence rates using a regional downscaling of future climate projections.

RESULTS

The spatial distribution of dengue fever cases is highly heterogeneous. The variables most associated with this observed heterogeneity are the mean temperature, the mean number of people per premise, and the mean percentage of unemployed people, a variable highly correlated with people's way of life. Rainfall does not seem to play an important role in the spatial distribution of dengue cases during epidemics. By the end of the 21st century, if temperature increases by approximately 3 °C, mean incidence rates during epidemics could double.

CONCLUSION

In New Caledonia, a subtropical insular environment, both temperature and socio-economic conditions are influencing the spatial spread of dengue fever. Extension of this study to other countries worldwide should improve the knowledge about climate influence on dengue burden and about the complex interplay between different factors. This study presents a methodology that can be used as a step by step guide to model dengue spatial heterogeneity in other countries.

Asymptomatic humans transmit dengue virus to mosquitoes

Three-quarters of the estimated 390 million dengue virus (DENV) infections each year are clinically inapparent. People with inapparent dengue virus infections are generally considered dead-end hosts for transmission because they do not reach sufficiently high viremia levels to infect mosquitoes. Here, we show that, despite their lower average level of viremia, asymptomatic people can be infectious to mosquitoes. Moreover, at a given level of viremia, DENV-infected people with no detectable symptoms or before the onset of symptoms are significantly more infectious to mosquitoes than people with symptomatic infections. Because DENV viremic people without clinical symptoms may be exposed to more mosquitoes through their undisrupted daily routines than sick people and represent the bulk of DENV infections, our data indicate that they have the potential to contribute significantly more to virus transmission to mosquitoes than previously recognized.

Yellow fever impact on brown howler monkeys (Alouatta guariba clamitans) in Argentina: a metamodelling approach based on population viability analysis and epidemiological dynamics

In South America, yellow fever (YF) is an established infectious disease that has been identified outside of its traditional endemic areas, affecting human and nonhuman primate (NHP) populations. In the epidemics that occurred in Argentina between 2007-2009, several outbreaks affecting humans and howler monkeys (Alouatta spp) were reported, highlighting the importance of this disease in the context of conservation medicine and public health policies. Considering the lack of information about YF dynamics in New World NHP, our main goal was to apply modelling tools to better understand YF transmission dynamics among endangered brown howler monkey (Alouatta guariba clamitans) populations in northeastern Argentina. Two complementary modelling tools were used to evaluate brown howler population dynamics in the presence of the disease: Vortex, a stochastic demographic simulation model, and Outbreak, a stochastic disease epidemiology simulation. The baseline model of YF disease epidemiology predicted a very high probability of population decline over the next 100 years. We believe the modelling approach discussed here is a reasonable description of the disease and its effects on the howler monkey population and can be useful to support evidence-based decision-making to guide actions at a regional level.

Progress and Challenges in Infectious Disease Cartography

Quantitatively mapping the spatial distributions of infectious diseases is key to both investigating their epidemiology and identifying populations at risk of infection. Important advances in data quality and methodologies have allowed for better investigation of disease risk and its association with environmental factors. However, incorporating dynamic human behavioural processes in disease mapping remains challenging. For example, connectivity among human populations, a key driver of pathogen dispersal, has increased sharply over the past century, along with the availability of data derived from mobile phones and other dynamic data sources. Future work must be targeted towards the rapid updating and dissemination of appropriately designed disease maps to guide the public health community in reducing the global burden of infectious disease.

Theory and data for simulating fine-scale human movement in an urban environment

Individual-based models of infectious disease transmission depend on accurate quantification of fine-scale patterns of human movement. Existing models of movement either pertain to overly coarse scales, simulate some aspects of movement but not others, or were designed specifically for populations in developed countries. Here, we propose a generalizable framework for simulating the locations that an individual visits, time allocation across those locations, and population-level variation therein. As a case study, we fit alternative models for each of five aspects of movement (number, distance from home and types of locations visited; frequency and duration of visits) to interview data from 157 residents of the city of Iquitos, Peru. Comparison of alternative models showed that location type and distance from home were significant determinants of the locations that individuals visited and how much time they spent there. We also found that for most locations, residents of two neighbourhoods displayed indistinguishable preferences for visiting locations at various distances, despite differing distributions of locations around those neighbourhoods. Finally, simulated patterns of time allocation matched the interview data in a number of ways, suggesting that our framework constitutes a sound basis for simulating fine-scale movement and for investigating factors that influence it.

Impact of human mobility on the emergence of dengue epidemics in Pakistan

The recent emergence of dengue viruses into new susceptible human populations throughout Asia and the Middle East, driven in part by human travel on both local and global scales, represents a significant global health risk, particularly in areas with changing climatic suitability for the mosquito vector. In Pakistan, dengue has been endemic for decades in the southern port city of Karachi, but large epidemics in the northeast have emerged only since 2011. Pakistan is therefore representative of many countries on the verge of countrywide endemic dengue transmission, where prevention, surveillance, and preparedness are key priorities in previously dengue-free regions. We analyze spatially explicit dengue case data from a large outbreak in Pakistan in 2013 and compare the dynamics of the epidemic to an epidemiological model of dengue virus transmission based on climate and mobility data from ∼40 million mobile phone subscribers. We find that mobile phone-based mobility estimates predict the geographic spread and timing of epidemics in both recently epidemic and emerging locations. We combine transmission suitability maps with estimates of seasonal dengue virus importation to generate fine-scale dynamic risk maps with direct application to dengue containment and epidemic preparedness.

Weather Regulates Location, Timing, and Intensity of Dengue Virus Transmission between Humans and Mosquitoes

Background

Dengue is one of the most aggressively expanding mosquito-transmitted viruses. The human burden approaches 400 million infections annually. Complex transmission dynamics pose challenges for predicting location, timing, and magnitude of risk; thus, models are needed to guide prevention strategies and policy development locally and globally. Weather regulates transmission-potential via its effects on vector dynamics. An important gap in understanding risk and roadblock in model development is an empirical perspective clarifying how weather impacts transmission in diverse ecological settings. We sought to determine if location, timing, and potential-intensity of transmission are systematically defined by weather.

Methodology/Principal Findings

We developed a high-resolution empirical profile of the local weather-disease connection across Peru, a country with considerable ecological diversity. Applying 2-dimensional weather-space that pairs temperature versus humidity, we mapped local transmission-potential in weather-space by week during 1994-2012. A binary classification-tree was developed to test whether weather data could classify 1828 Peruvian districts as positive/negative for transmission and into ranks of transmission-potential with respect to observed disease. We show that transmission-potential is regulated by temperature-humidity coupling, enabling epidemics in a limited area of weather-space. Duration within a specific temperature range defines transmission-potential that is amplified exponentially in higher humidity. Dengue-positive districts were identified by mean temperature >22°C for 7+ weeks and minimum temperature >14°C for 33+ weeks annually with 95% sensitivity and specificity. In elevated-risk locations, seasonal peak-incidence occurred when mean temperature was 26-29°C, coincident with humidity at its local maximum; highest incidence when humidity >80%. We profile transmission-potential in weather-space for temperature-humidity ranging 0-38°C and 5-100% at 1°C x 2% resolution.

Conclusions/Significance

Local duration in limited areas of temperature-humidity weather-space identifies potential locations, timing, and magnitude of transmission. The weather-space profile of transmission-potential provides needed data that define a systematic and highly-sensitive weather-disease connection, demonstrating separate but coupled roles of temperature and humidity. New insights regarding natural regulation of human-mosquito transmission across diverse ecological settings advance our understanding of risk locally and globally for dengue and other mosquito-borne diseases and support advances in public health policy/operations, providing an evidence-base for modeling, predicting risk, and surveillance-prevention planning.

Timing and spatial-extent of diseases such as dengue and malaria that result from transmission between humans and mosquitoes are regulated by weather in complicated ways. For Aedes aegypti mosquitoes, the primary vector of dengue, slight changes in different components of weather have important effects on population dynamics, lifespan, biting-frequency, virus incubation period and capacity to transmit the virus, thus inducing changes in transmission probability. These complicated dynamics produce a weather-disease connection that is not well-defined for different ecological settings. Understanding this connection is important to critical elements of policy development and operational control of dengue such as predicting risk, developing human-vector transmission models, and planning surveillance-intervention strategies locally and globally. The empirical profile of the weather-disease connection for dengue developed in this study provides a needed understanding of how temperature and humidity work together in regulating human-mosquito transmission. The observed likelihood of low to epidemic-level transmission was highly sensitive to local seasonal duration in limited areas of this two-dimensional weather-space. Data presented represent a resource for estimating where and when transmission-potential supports epidemics of varying magnitude. This high-resolution weather-disease profile for dengue reveals systematic relationships that are informative for mosquito-borne diseases in general and discussions of consequences of global warming.

Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa

Simple spatial interaction models of human mobility based on physical laws have been used extensively in the social, biological, and physical sciences, and in the study of the human dynamics underlying the spread of disease. Recent analyses of commuting patterns and travel behavior in high-income countries have led to the suggestion that these models are highly generalizable, and as a result, gravity and radiation models have become standard tools for describing population mobility dynamics for infectious disease epidemiology. Communities in Sub-Saharan Africa may not conform to these models, however; physical accessibility, availability of transport, and cost of travel between locations may be variable and severely constrained compared to high-income settings, informal labor movements rather than regular commuting patterns are often the norm, and the rise of mega-cities across the continent has important implications for travel between rural and urban areas. Here, we first review how infectious disease frameworks incorporate human mobility on different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to analyze the spatiotemporal dynamics of the Kenyan population. We find that gravity and radiation models fail in systematic ways to capture human mobility measured by mobile phones; both severely overestimate the spatial spread of travel and perform poorly in rural areas, but each exhibits different characteristic patterns of failure with respect to routes and volumes of travel. Thus, infectious disease frameworks that rely on spatial interaction models are likely to misrepresent population dynamics important for the spread of disease in many African populations.

Human mobility underlies many social, biological, and physical phenomena, including the spread of infectious diseases. Analyses in high-income countries have led to the notion that populations obey universal rules of mobility that are effectively captured by spatial interaction models. However, communities in Africa may not conform to these rules since the availability of transport and geographic barriers may impose different constraints compared to high-income settings. We use anonymous mobile phone data from ~15 million subscribers to quantify different spatial and temporal scales of mobility within Kenya and test their performance with respect to this measurement of human travel. We find that standard models systematically fail to describe regional mobility in Kenya, with poor performance in rural areas. Epidemiological models that rely on these frameworks may therefore fail to capture important aspects of population dynamics driving disease spread in many African populations.

Models for the effects of host movement in vector-borne disease systems

Host and/or vector movement patterns have been shown to have significant effects in both empirical studies and mathematical models of vector-borne diseases. The processes of economic development and globalization seem likely to make host movement even more important in the future. This article is a brief survey of some of the approaches that have been used to study the effects of host movement in analytic mathematical models for vector-borne diseases. It describes the formulation and interpretation of various types of spatial models and describes a few of the conclusions that can be drawn from them. It is not intended to be comprehensive but rather to provide sufficient background material and references to the literature to serve as an entry point into this area of research for interested readers.

Assessing the epidemiological effect of wolbachia for dengue control

Dengue viruses cause more human morbidity and mortality than any other arthropod-borne virus. Dengue prevention relies mainly on vector control; however, the failure of traditional methods has promoted the development of novel entomological approaches. Although use of the intracellular bacterium wolbachia to control mosquito populations was proposed 50 years ago, only in the past decade has its use as a potential agent of dengue control gained substantial interest. Here, we review evidence that supports a practical approach for dengue reduction through field release of wolbachia-infected mosquitoes and discuss the additional studies that have to be done before the strategy can be validated and implemented. A crucial next step is to assess the efficacy of wolbachia in reducing dengue virus transmission. We argue that a cluster randomised trial is at this time premature because choice of wolbachia strain for release and deployment strategies are still being optimised. We therefore present a pragmatic approach to acquiring preliminary evidence of efficacy through various complementary methods including a prospective cohort study, a geographical cluster investigation, virus phylogenetic analysis, virus surveillance in mosquitoes, and vector competence assays. This multipronged approach could provide valuable intermediate evidence of efficacy to justify a future cluster randomised trial.

Improving dengue virus capture rates in humans and vectors in Kamphaeng Phet Province, Thailand, using an enhanced spatiotemporal surveillance strategy

Dengue is of public health importance in tropical and sub-tropical regions. Dengue virus (DENV) transmission dynamics was studied in Kamphaeng Phet Province, Thailand, using an enhanced spatiotemporal surveillance of 93 hospitalized subjects with confirmed dengue (initiates) and associated cluster individuals (associates) with entomologic sampling. A total of 438 associates were enrolled from 208 houses with household members with a history of fever, located within a 200-m radius of an initiate case. Of 409 associates, 86 (21%) had laboratory-confirmed DENV infection. A total of 63 (1.8%) of the 3,565 mosquitoes collected were dengue polymerase chain reaction positive (PCR+). There was a significant relationship between spatial proximity to the initiate case and likelihood of detecting DENV from associate cases and Aedes mosquitoes. The viral detection rate from human hosts and mosquito vectors in this study was higher than previously observed by the study team in the same geographic area using different methodologies. We propose that the sampling strategy used in this study could support surveillance of DENV transmission and vector interactions.

A household serosurvey to estimate the magnitude of a dengue outbreak in Mombasa, Kenya, 2013

Dengue appears to be endemic in Africa with a number of reported outbreaks. In February 2013, several individuals with dengue-like illnesses and negative malaria blood smears were identified in Mombasa, Kenya. Dengue was laboratory confirmed and an investigation was conducted to estimate the magnitude of local transmission including a serologic survey to determine incident dengue virus (DENV) infections. Consenting household members provided serum and were questioned regarding exposures and medical history. RT-PCR was used to identify current DENV infections and IgM anti-DENV ELISA to identify recent infections. Of 1,500 participants from 701 households, 210 (13%) had evidence of current or recent DENV infection. Among those infected, 93 (44%) reported fever in the past month. Most (68, 73%) febrile infected participants were seen by a clinician and all but one of 32 participants who reportedly received a diagnosis were clinically diagnosed as having malaria. Having open windows at night (OR = 2.3; CI: 1.1-4.8), not using daily mosquito repellent (OR = 1.6; CI: 1.0-2.8), and recent travel outside of Kenya (OR = 2.5; CI: 1.1-5.4) were associated with increased risk of DENV infection. This survey provided a robust measure of incident DENV infections in a setting where cases were often unrecognized and misdiagnosed.

Clustering, climate and dengue transmission

Dengue is currently the most rapidly spreading vector-borne disease, with an increasing burden over recent decades. Currently, neither a licensed vaccine nor an effective anti-viral therapy is available, and treatment largely remains supportive. Current vector control strategies to prevent and reduce dengue transmission are neither efficient nor sustainable as long-term interventions. Increased globalization and climate change have been reported to influence dengue transmission. In this article, we reviewed the non-climatic and climatic risk factors which facilitate dengue transmission. Sustainable and effective interventions to reduce the increasing threat from dengue would require the integration of these risk factors into current and future prevention strategies, including dengue vaccination, as well as the continuous support and commitment from the political and environmental stakeholders.

Comparison of BG-Sentinel® Trap and Oviposition Cups for Aedes aegypti and Aedes albopictus Surveillance in Jacksonville, Florida, USA

The BG-Sentinel® (BGS) trap and oviposition cups (OCs) have both proven effective in the surveillance of Aedes species. This study aimed to determine which of the 2 traps could best characterize the relative population sizes of Aedes albopictus and Aedes aegypti in an urban section of Jacksonville, FL. Until 1986, Ae. aegypti was considered the dominant container-breeding species in urban northeastern Florida. Since the introduction of Ae. albopictus, Ae. aegypti has become almost completely extirpated. In 2011, a resurgence of Ae. aegypti was detected in the urban areas of Jacksonville; thus this study initially set out to determine the extent of Ae. aegypti reintroduction to the area. We determined that the BGS captured a greater number of adult Ae. aegypti than Ae. albopictus, while OCs did not monitor significantly different numbers of either species, even in areas where the BGS traps suggested a predominance of one species over the other. Both traps were effective at detecting Aedes spp.; however, the BGS proved more diverse by detecting over 20 other species as well. Our results show that in order to accurately determine vectorborne disease threats and the impact of control operations on these 2 species, multiple trapping techniques should be utilized when studying Ae. aegypti and Ae. albopictus population dynamics.

Utility of mosquito surveillance data for spatial prioritization of vector control against dengue viruses in three Brazilian cities

Background

Vector control remains the primary defense against dengue fever. Its success relies on the assumption that vector density is related to disease transmission. Two operational issues include the amount by which mosquito density should be reduced to minimize transmission and the spatio-temporal allotment of resources needed to reduce mosquito density in a cost-effective manner. Recently, a novel technology, MI-Dengue, was implemented city-wide in several Brazilian cities to provide real-time mosquito surveillance data for spatial prioritization of vector control resources. We sought to understand the role of city-wide mosquito density data in predicting disease incidence in order to provide guidance for prioritization of vector control work.

Methods

We used hierarchical Bayesian regression modeling to examine the role of city-wide vector surveillance data in predicting human cases of dengue fever in space and time. We used four years of weekly surveillance data from Vitoria city, Brazil, to identify the best model structure. We tested effects of vector density, lagged case data and spatial connectivity. We investigated the generality of the best model using an additional year of data from Vitoria and two years of data from other Brazilian cities: Governador Valadares and Sete Lagoas.

Results

We found that city-wide, neighborhood-level averages of household vector density were a poor predictor of dengue-fever cases in the absence of accounting for interactions with human cases. Effects of city-wide spatial patterns were stronger than within-neighborhood or nearest-neighborhood effects. Readily available proxies of spatial relationships between human cases, such as economic status, population density or between-neighborhood roadway distance, did not explain spatial patterns in cases better than unweighted global effects.

Conclusions

For spatial prioritization of vector controls, city-wide spatial effects should be given more weight than within-neighborhood or nearest-neighborhood connections, in order to minimize city-wide cases of dengue fever. More research is needed to determine which data could best inform city-wide connectivity. Once these data become available, MI-dengue may be even more effective if vector control is spatially prioritized by considering city-wide connectivity between cases together with information on the location of mosquito density and infected mosquitos.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-015-0659-y) contains supplementary material, which is available to authorized users.

Daily forecast of dengue fever incidents for urban villages in a city

Background

Instead of traditional statistical models for large spatial areas and weekly or monthly temporal units, what public health workers urgently need is a timely risk prediction method for small areas. This risk prediction would provide information for early warning, target surveillance and intervention.

Methods

Daily dengue cases in the 457 urban villages of Kaohsiung City, Taiwan from 2009 to 2012 were used for model development and evaluation. There were in total 2,997 confirmed dengue cases during this period. A logistic regression model was fitted to the daily incidents occurring in the villages for the past 30 days. The fitted model was then used to predict the incidence probabilities of dengue outbreak for the villages the next day. A percentile of the 457*30 fitted incidence probabilities was chosen to determine a cut-point for issuing the alerts. The covariates included three different levels of spatial effect, and with four lag time periods. The population density and the meteorological conditions were also included for the prediction.

Results

The performance of the prediction models was evaluated on 122 consecutive days from September 1 to December 31, 2012. With the 80th percentile threshold, the median sensitivity was 83% and the median false positive rate was 23%. We found that most of the coefficients of the predictors of having cases at the same village in the previous 14 days were positive and significant for the 122 daily updated models. The estimated coefficients of population density were significant during the peak of the epidemic in 2012.

Conclusions

The proposed method can provide near real-time dengue risk prediction for a small area. This can serve as a useful decision making tool for front-line public health workers to control dengue epidemics. The precision of the spatial and temporal units can be easily adjusted to different settings for different cities.

Dengue

Dengue viruses have spread rapidly within countries and across regions in the past few decades, resulting in an increased frequency of epidemics and severe dengue disease, hyperendemicity of multiple dengue virus serotypes in many tropical countries, and autochthonous transmission in Europe and the USA. Today, dengue is regarded as the most prevalent and rapidly spreading mosquito-borne viral disease of human beings. Importantly, the past decade has also seen an upsurge in research on dengue virology, pathogenesis, and immunology and in development of antivirals, vaccines, and new vector-control strategies that can positively impact dengue control and prevention.

Network-based vaccination improves prospects for disease control in wild chimpanzees

Many endangered wildlife populations are vulnerable to infectious diseases for which vaccines exist; yet, pragmatic considerations often preclude large-scale vaccination efforts. These barriers could be reduced by focusing on individuals with the highest contact rates. However, the question then becomes whether targeted vaccination is sufficient to prevent large outbreaks. To evaluate the efficacy of targeted wildlife vaccinations, we simulate pathogen transmission and control on monthly association networks informed by behavioural data from a wild chimpanzee community (Kanyawara N = 37, Kibale National Park, Uganda). Despite considerable variation across monthly networks, our simulations indicate that targeting the most connected individuals can prevent large outbreaks with up to 35% fewer vaccines than random vaccination. Transmission heterogeneities might be attributed to biological differences among individuals (e.g. sex, age, dominance and family size). Thus, we also evaluate the effectiveness of a trait-based vaccination strategy, as trait data are often easier to collect than interaction data. Our simulations indicate that a trait-based strategy can prevent large outbreaks with up to 18% fewer vaccines than random vaccination, demonstrating that individual traits can serve as effective estimates of connectivity. Overall, these results suggest that fine-scale behavioural data can help optimize pathogen control efforts for endangered wildlife.

A network-patch methodology for adapting agent-based models for directly transmitted disease to mosquito-borne disease

Mosquito-borne diseases cause significant public health burden and are widely re-emerging or emerging. Understanding, predicting, and mitigating the spread of mosquito-borne disease in diverse populations and geographies are ongoing modelling challenges. We propose a hybrid network-patch model for the spread of mosquito-borne pathogens that accounts for individual movement through mosquito habitats, extending the capabilities of existing agent-based models (ABMs) to include vector-borne diseases. The ABM are coupled with differential equations representing 'clouds' of mosquitoes in patches accounting for mosquito ecology. We adapted an ABM for humans using this method and investigated the importance of heterogeneity in pathogen spread, motivating the utility of models of individual behaviour. We observed that the final epidemic size is greater in patch models with a high risk patch frequently visited than in a homogeneous model. Our hybrid model quantifies the importance of the heterogeneity in the spread of mosquito-borne pathogens, guiding mitigation strategies.