Defining the Risk of Zika and Chikungunya Virus Transmission in Human Population Centers of the Eastern United States

Clinical description of dengue and chikungunya virus infections amongst acute febrile patients in a malaria endemic area of Mfou, the Centre region of Cameroon

This study aims to determine the frequency and clinical manifestations of dengue and chikungunya viral infections in the district hospital of Mfou, Centre region of Cameroon where malaria is endemic. Blood samples were collected from suspected cases and tested for Plasmodium parasites and for the molecular detection of viral RNAs (dengue, zika and chikungunya viruses) using TRIOPLEX qPCR. A total of 108 patients were clinically suspected among which 25 % were male and 50 % were less than 15.5 years old. Of these 14.8 % (16/108) and 2.8 % (3/108) had acute dengue and chikungunya fevers respectively. Co-infection with malaria was reported in 56.3 % (9/16) of Dengue cases and 33.3 % (1/3) of chikungunya cases. Clinical profiling further revealed that nausea and vomiting show a significant difference in dengue infected individuals to those of non-infected individuals (P = 0.027). The presence of dengue fever and chikungunya fever and the absence of specific clinical manifestations highlight the need to strengthen surveillance of acute febrile infections for a better estimation of the burden of arboviruses.

Assessing the impact of emergency measures in varied population density areas during a large dengue outbreak

Background

The patterns of dengue are affected by many factors, including population density and climate factors. Densely populated areas could play a role in dengue transmission due to increased human-mosquito contacts, the presence of more diverse and suitable vector habitats and breeding sites, and changes in land use. In addition to population densities, climatic factors such as temperature, relative humidity, and precipitation have been demonstrated to predict dengue patterns. To control dengue, emergency measures should focus on vector management. Most approaches to assessing emergency responses to dengue risks involve applying simulation models or describing emergency activities and the results of implementing those responses. Research using real-world data with analytical methods to evaluate emergency responses to dengue has been limited. This study investigated emergency control measures associated with dengue risks in areas with high and low population densities, considering their different control capacities.

Methodology

Data from the 2015 dengue outbreak in Kaohsiung City, Taiwan, were utilized. The government database provided information on confirmed dengue cases, emergency control measures, and climatic data. The study employed a distributed lag non-linear model (DLNM) to assess the effect of emergency control measures and their time lags on dengue risk.

Principal findings

The findings revealed that in areas with high population density, the absence of emergency measures significantly elevated the risks of dengue. However, implementing emergency measures, especially a higher number, was associated with lower risks. In contrast, in areas with low population density, the risks of dengue were only significantly elevated at the 1st week lag if no emergency control measures were implemented. When emergency activities were carried out, the risks of dengue significantly decreased only for the 1st week lag.

Conclusions

Our findings reveal distinct exposure-lag-response patterns in the associations between emergency control measures and dengue in areas with high and low population density. In regions with a high population density, implementing emergency activities during a significant dengue outbreak is crucial for reducing the risk. Conversely, in areas of low population density, the necessity of applying emergency activities may be less pronounced. The implications of this study on dengue management could provide valuable insights for health authorities dealing with limited resources.

The analysis of a new fractional model to the Zika virus infection with mutant

We present a new mathematical model to analyze the dynamics of the Zika virus (ZV) disease with the mutant under the real confirmed cases in Colombia. We give the formulation of the model initially in integer order derivative and then extend it to a fractional order system in the sense of the Mittag-Leffler kernel. We study the properties of the model in the Mittag-Leffler kernel and establish the result. The basic reproduction of the fractional system is computed. The equilibrium points of the Zika virus model are obtained and found that the endemic equilibria exist when the threshold is greater than unity. Further, we show that the model does not possess the backward bifurcation phenomenon. The numerical procedure to solve the problem using the Atangana-Baleanu derivative is shown using the newly established numerical scheme. We consider the real cases of the Zika virus in Colombia outbreak are considered and simulate the model using the nonlinear least square curve fit and computed the basic reproduction number R 0 = 0.4942 , whereas in previous work (Alzahrani et al., 2021) [1], the authors computed the basic reproduction number R 0 = 0.5447 . This is due to the fact that our work in the present paper provides better fitting to the data when using the fractional order model, and indeed the result regarding the data fitting using the fractional model is better than integer order model. We give a sensitivity analysis of the parameters involved in the basic reproduction number and show them graphically. The results obtained through the present numerical method converge to its equilibrium for the fractional order, indicating the proposed scheme's reliability.

Comparing Satellite and Ground-Based Measurements of Environmental Suitability for Vector Mosquitoes in an Urban Landscape

Exposure to mosquito-borne diseases is influenced by landscape patterns and microclimates associated with land cover. These influences can be particularly strong in heterogeneous urban landscapes where human populations are concentrated. We investigated how land cover and climate influenced abundances of Ae. albopictus (Skuse) (Diptera: Culicidae) and Cx. quinquefasciatus (Say) (Diptera: Culicidae) in Norman, Oklahoma (United States). From June-October 2019 and May-October 2020 we sampled mosquitoes along an urban-rural gradient using CO2 baited BG Sentinel traps. Microclimate sensors at these sites measured temperature and humidity. We mapped environmental variables using satellite images from Landsat, Sentinel-2, and VIIRS, and the CHIRPS rainfall dataset. We also obtained meteorological data from the closest weather station. We compared statistical models of mosquito abundance based on microclimate, satellite, weather station, and land cover data. Mosquitoes were more abundant on trap days with higher temperature and relative humidity. Rainfall 2 wk prior to the trap day negatively affected mosquito abundances. Impervious surface cover was positively associated with Cx. quinquefasciatus and tree cover was negatively associated with Ae. albopictus. Among the data sources, models based on satellite variables and land cover data had the best fits for Ae. albopictus (R2 = 0.7) and Cx. quinquefasciatus (R2 = 0.51). Models based on weather station or microclimate data had weaker fits (R2 between 0.09 and 0.17) but were improved by adding land cover variables (R2 between 0.44 and 0.61). These results demonstrate the potential for using satellite remote sensing for mosquito habitat analyses in urban areas.

Changes in Container-Breeding Mosquito Diversity and Abundance Along an Urbanization Gradient are Associated With Dominance of Arboviral Vectors

Environmental conditions associated with urbanization are likely to influence the composition and abundance of mosquito (Diptera, Culicidae) assemblages through effects on juvenile stages, with important consequences for human disease risk. We present six years (2011-2016) of weekly juvenile mosquito data from distributed standardized ovitraps and evaluate how variation in impervious cover and temperature affect the composition and abundance of container-breeding mosquito species in Maryland, USA. Species richness and evenness were lowest at sites with high impervious cover (>60% in 100-m buffer). However, peak diversity was recorded at sites with intermediate impervious cover (28-35%). Four species were observed at all sites, including two recent invasives (Aedes albopictus Skuse, Ae. japonicus Theobald), an established resident (Culex pipiens L), and one native (Cx. restuans Theobald). All four are viral vectors in zoonotic or human transmission cycles. Temperature was a positive predictor of weekly larval abundance during the growing season for each species, as well as a positive predictor of rapid pupal development. Despite being observed at all sites, each species responded differently to impervious cover. Abundance of Ae. albopictus larvae was positively associated with impervious cover, emphasizing that this medically-important vector not only persists in the warmer, impervious urban landscape but is positively associated with it. Positive temperature effects in our models of larval abundance and pupae occurrence in container habitats suggest that these four vector species are likely to continue to be present and abundant in temperate cities under future temperature scenarios.

How public reaction to disease information across scales and the impacts of vector control methods influence disease prevalence and control efficacy

With the development of social media, the information about vector-borne disease incidence over broad spatial scales can cause demand for local vector control before local risk exists. Anticipatory intervention may still benefit local disease control efforts; however, infection risks are not the only focal concerns governing public demand for vector control. Concern for environmental contamination from pesticides and economic limitations on the frequency and magnitude of control measures also play key roles. Further, public concern may be focused more on ecological factors (i.e., controlling mosquito populations) or on epidemiological factors (i.e., controlling infection-carrying mosquitoes), which may lead to very different control outcomes. Here we introduced a generic Ross-MacDonald model, incorporating these factors under three spatial scales of disease information: local, regional, and global. We tailored and parameterized the model for Zika virus transmitted by Aedes aegypti mosquito. We found that sensitive reactivity caused by larger-scale incidence information could decrease average human infections per patch breeding capacity, however, the associated increase in total control effort plays a larger role, which leads to an overall decrease in control efficacy. The shift of focal concerns from epidemiological to ecological risk could relax the negative effect of the sensitive reactivity on control efficacy when mosquito breeding capacity populations are expected to be large. This work demonstrates that, depending on expected total mosquito breeding capacity population size, and weights of different focal concerns, large-scale disease information can reduce disease infections without lowering control efficacy. Our findings provide guidance for vector-control strategies by considering public reaction through social media.

Chikungunya Beyond the Tropics: Where and When Do We Expect Disease Transmission in Europe?

Chikungunya virus disease (chikungunya) is a mosquito-borne infectious disease reported in at least 50 countries, mostly in the tropics. It has spread around the globe within the last two decades, with local outbreaks in Europe. The vector mosquito Aedes albopictus (Diptera, Culicidae) has already widely established itself in southern Europe and is spreading towards central parts of the continent. Public health authorities and policymakers need to be informed about where and when a chikungunya transmission is likely to take place. Here, we adapted a previously published global ecological niche model (ENM) by including only non-tropical chikungunya occurrence records and selecting bioclimatic variables that can reflect the temperate and sub-tropical conditions in Europe with greater accuracy. Additionally, we applied an epidemiological model to capture the temporal outbreak risk of chikungunya in six selected European cities. Overall, the non-tropical ENM captures all the previous outbreaks in Europe, whereas the global ENM had underestimated the risk. Highly suitable areas are more widespread than previously assumed. They are found in coastal areas of the Mediterranean Sea, in the western part of the Iberian Peninsula, and in Atlantic coastal areas of France. Under a worst-case scenario, even large areas of western Germany and the Benelux states are considered potential areas of transmission. For the six selected European cities, June–September (the 22th–38th week) is the most vulnerable time period, with the maximum continuous duration of a possible transmission period lasting up to 93 days (Ravenna, Italy).

Host interactions of Aedes albopictus, an invasive vector of arboviruses, in Virginia, USA

Background

As an invasive mosquito species in the United States, Aedes albopictus is a potential vector of arboviruses including dengue, chikungunya, and Zika, and may also be involved in occasional transmission of other arboviruses such as West Nile, Saint Louis encephalitis, eastern equine encephalitis, and La Crosse viruses. Aedes albopictus feeds on a wide variety of vertebrate hosts, wild and domestic, as well as humans.

Methodology/Principal findings

In order to investigate blood feeding patterns of Ae. albopictus, engorged specimens were collected from a variety of habitat types using the Centers for Disease Control and Prevention light traps, Biogents Sentinel 2 traps, and modified Reiter gravid traps in southeast Virginia. Sources of blood meals were determined by the analysis of mitochondrial cytochrome b gene sequences amplified in PCR assays. Our aims were to quantify degrees of Ae. albopictus interactions with vertebrate hosts as sources of blood meals, investigate arboviral infection status, assess the influence of key socioecological conditions on spatial variability in blood feeding, and investigate temporal differences in blood feeding by season. Analysis of 961 engorged specimens of Ae. albopictus sampled between 2017–2019 indicated that 96%, 4%, and less than 1% obtained blood meals from mammalian, reptilian, and avian hosts, respectively. Domestic cats were the most frequently identified (50.5%) hosts followed by Virginia opossums (17.1%), white-tailed deer (12.2%), and humans (7.3%), together representing 87.1% of all identified blood hosts. We found spatial patterns in blood feeding linked to socioecological conditions and seasonal shifts in Ae. albopictus blood feeding with implications for understanding human biting and disease risk. In Suffolk Virginia in areas of lower human development, the likelihood of human blood feeding increased as median household income increased and human blood feeding was more likely early in the season (May-June) compared to later (July-October). Screening of the head and thorax of engorged Ae. albopictus mosquitoes by cell culture and RT-PCR resulted in a single isolate of Potosi virus.

Conclusion and significance

Understanding mosquito-host interactions in nature is vital for evaluating vectorial capacity of mosquitoes. These interactions with competent reservoir hosts support transmission, maintenance, and amplification of zoonotic agents of human diseases. Results of our study in conjunction with abundance in urban/suburban settings, virus isolation from field-collected mosquitoes, and vector competence of Ae. albopictus, highlight the potential involvement of this species in the transmission of a number of arboviruses such as dengue, chikungunya, and Zika to humans. Limited interaction with avian hosts suggests that Ae. albopictus is unlikely to serve as a bridge vector of arboviruses such as West Nile and eastern equine encephalitis in the study region, but that possibility cannot be entirely ruled out.

Native to Southeast Asia, breeding populations of Aedes albopictus were first discovered in Harris County, Texas, in 1985, and as of 2017, seasonal populations of this species have been reported in more than 40 states and the District of Columbia. Aedes albopictus breed readily in natural or man-made environment where stagnant water can accumulate such as gutters, flowerpots, discarded tires, and tree holes. This mosquito species has been implicated in outbreaks of chikungunya, dengue, and Zika viruses and is a competent vector of many arboviruses including West Nile, eastern equine encephalitis, yellow fever, Rift Valley fever, and Japanese encephalitis. Aedes albopictus is regarded as an opportunistic mosquito feeding on a variety of domestic and wild mammals, birds, reptiles and amphibians; however, a preference for human blood meals has been noted in blood meal analysis of field-collected mosquitoes and in laboratory investigations. We studied vector-host interactions of Ae. albopictus in Virginia, United States using molecular methods and identified ten mammalian, three reptilian, and two avian species as blood hosts of this mosquito species. Our study clarifies the host associations of Ae. albopictus and highlights concerns about the potential role of this mosquito species in transmission of emerging and reemerging arboviruses.

Nonlinear self-organized population dynamics induced by external selective nonlocal processes

Self-organization evolution of a population is studied considering generalized reaction-diffusion equations. We proposed a model based on non-local operators that has several of the equations traditionally used in research on population dynamics as particular cases. Then, employing a relatively simple functional form of the non-local kernel, we determined the conditions under which the analyzed population develops spatial patterns, as well as their main characteristics. Finally, we established a relationship between the developed model and real systems by making simulations of bacterial populations subjected to non-homogeneous lighting conditions. Our proposal reproduces some of the experimental results that other approaches considered previously had not been able to obtain.

Warming temperatures could expose more than 1.3 billion new people to Zika virus risk by 2050

In the aftermath of the 2015 pandemic of Zika virus (ZIKV), concerns over links between climate change and emerging arboviruses have become more pressing. Given the potential that much of the world might remain at risk from the virus, we used a previously established temperature-dependent transmission model for ZIKV to project climate change impacts on transmission suitability risk by mid-century (a generation into the future). Based on these model predictions, in the worst-case scenario, over 1.3 billion new people could face suitable transmission temperatures for ZIKV by 2050. The next generation will face substantially increased ZIKV transmission temperature suitability in North America and Europe, where naïve populations might be particularly vulnerable. Mitigating climate change even to moderate emissions scenarios could significantly reduce global expansion of climates suitable for ZIKV transmission, potentially protecting around 200 million people. Given these suitability risk projections, we suggest an increased priority on research establishing the immune history of vulnerable populations, modeling when and where the next ZIKV outbreak might occur, evaluating the efficacy of conventional and novel intervention measures, and increasing surveillance efforts to prevent further expansion of ZIKV.

Optimization of the Controls against the Spread of Zika Virus in Populations

In this paper, we study and explore two control strategies to decrease the spread of Zika virus in the human and mosquito populations. The control strategies that we consider in this study are awareness and spraying campaigns. We solve several optimal control problems relying on a mathematical epidemic model of Zika that considers both human and mosquito populations. The first control strategy is broad and includes using information campaigns, encouraging people to use bednetting, wear long-sleeve shirts, or similar protection actions. The second control is more specific and relies on spraying insecticides. The control system relies on a Zika mathematical model with control functions. To develop the optimal control problem, we use Pontryagins’ maximum principle, which is numerically solved as a boundary value problem. For the mathematical model of the Zika epidemic, we use parameter values extracted from real data from an outbreak in Colombia. We study the effect of the costs related to the controls and infected populations. These costs are important in real life since they can change the outcomes and recommendations for health authorities dramatically. Finally, we explore different options regarding which control measures are more cost-efficient for society.

Coordination among neighbors improves the efficacy of Zika control despite economic costs

Emerging mosquito-borne viruses like Zika, dengue, and chikungunya pose a major threat to public health, especially in low-income regions of Central and South America, southeast Asia, and the Caribbean. Outbreaks of these diseases are likely to have long-term social and economic consequences due to Zika-induced congenital microcephaly and other complications. Larval control of the container-inhabiting mosquitoes that transmit these infections is an important tool for mitigating outbreaks. However, metapopulation theory suggests that spatiotemporally uneven larvicide treatment can impede control effectiveness, as recolonization compensates for mortality within patches. Coordinating the timing of treatment among patches could therefore substantially improve epidemic control, but we must also consider economic constraints, since coordination may have costs that divert resources from treatment. To inform practical disease management strategies, we ask how coordination among neighbors in the timing of mosquito control efforts influences the size of a mosquito-borne infectious disease outbreak under the realistic assumption that coordination has costs. Using an SIR (Susceptible-Infectious-Recovered)/metapopulation model of mosquito and disease dynamics, we examine whether sharing surveillance information and coordinating larvicide treatment among neighboring patches reduces human infections when incorporating coordination costs. We examine how different types of coordination costs and different surveillance methods jointly influence the effectiveness of larval control. We find that the effect of coordination depends on both costs and the type of surveillance used to inform treatment. With epidemiological surveillance, coordination improves disease outcomes, even when costly. With demographic surveillance, coordination either improves or hampers disease control, depending on the type of costs and surveillance sensitivity. Our results suggest coordination among neighbors can improve management of mosquito-borne epidemics under many, but not all, assumptions about costs. Therefore, estimating coordination costs is an important step for most effectively applying metapopulation theory to strategies for managing outbreaks of mosquito-borne viral infections.

RETRACTED: The role of antibiotics in the preparation of antitumor drugs under fuzzy system

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219320.

Reviewing estimates of the basic reproduction number for dengue, Zika and chikungunya across global climate zones

BACKGROUND

Globally, dengue, Zika virus, and chikungunya are important viral mosquito-borne diseases that infect millions of people annually. Their geographic range includes not only tropical areas but also sub-tropical and temperate zones such as Japan and Italy. The relative severity of these arboviral disease outbreaks can vary depending on the setting. In this study we explore variation in the epidemiologic potential of outbreaks amongst these climatic zones and arboviruses in order to elucidate potential reasons behind such differences.

METHODOLOGY

We reviewed the peer-reviewed literature (PubMed) to obtain basic reproduction number (R₀) estimates for dengue, Zika virus, and chikungunya from tropical, sub-tropical and temperate regions. We also computed R₀ estimates for temperate and sub-tropical climate zones, based on the outbreak curves in the initial outbreak phase. Lastly we compared these estimates across climate zones, defined by latitude.

RESULTS

Of 2115 studies, we reviewed the full text of 128 studies and included 65 studies in our analysis. Our results suggest that the R₀ of an arboviral outbreak depends on climate zone, with lower R₀ estimates, on average, in temperate zones (R₀ = 2.03) compared to tropical (R₀ = 3.44) and sub-tropical zones (R₀ = 10.29). The variation in R₀ was considerable, ranging from 0.16 to 65. The largest R₀ was for dengue (65) and was estimated by the Ross-Macdonald model in the tropical zone, whereas the smallest R₀ (0.16) was for Zika virus and was estimated statistically from an outbreak curve in the sub-tropical zone.

CONCLUSIONS

The results indicate climate zone to be an important determinant of the basic reproduction number, R₀, for dengue, Zika virus, and chikungunya. The role of other factors as determinants of R₀, such as methods, environmental and social conditions, and disease control, should be further investigated. The results suggest that R₀ may increase in temperate regions in response to global warming, and highlight the increasing need for strengthening preparedness and control activities.

A systematic review and evaluation of Zika virus forecasting and prediction research during a public health emergency of international concern

INTRODUCTION

Epidemic forecasting and prediction tools have the potential to provide actionable information in the midst of emerging epidemics. While numerous predictive studies were published during the 2016-2017 Zika Virus (ZIKV) pandemic, it remains unknown how timely, reproducible, and actionable the information produced by these studies was.

METHODS

To improve the functional use of mathematical modeling in support of future infectious disease outbreaks, we conducted a systematic review of all ZIKV prediction studies published during the recent ZIKV pandemic using the PRISMA guidelines. Using MEDLINE, EMBASE, and grey literature review, we identified studies that forecasted, predicted, or simulated ecological or epidemiological phenomena related to the Zika pandemic that were published as of March 01, 2017. Eligible studies underwent evaluation of objectives, data sources, methods, timeliness, reproducibility, accessibility, and clarity by independent reviewers.

RESULTS

2034 studies were identified, of which n = 73 met the eligibility criteria. Spatial spread, R0 (basic reproductive number), and epidemic dynamics were most commonly predicted, with few studies predicting Guillain-Barré Syndrome burden (4%), sexual transmission risk (4%), and intervention impact (4%). Most studies specifically examined populations in the Americas (52%), with few African-specific studies (4%). Case count (67%), vector (41%), and demographic data (37%) were the most common data sources. Real-time internet data and pathogen genomic information were used in 7% and 0% of studies, respectively, and social science and behavioral data were typically absent in modeling efforts. Deterministic models were favored over stochastic approaches. Forty percent of studies made model data entirely available, 29% provided all relevant model code, 43% presented uncertainty in all predictions, and 54% provided sufficient methodological detail to allow complete reproducibility. Fifty-one percent of predictions were published after the epidemic peak in the Americas. While the use of preprints improved the accessibility of ZIKV predictions by a median of 119 days sooner than journal publication dates, they were used in only 30% of studies.

CONCLUSIONS

Many ZIKV predictions were published during the 2016-2017 pandemic. The accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied and indicates there is substantial room for improvement. To enhance the utility of analytical tools for outbreak response it is essential to improve the sharing of model data, code, and preprints for future outbreaks, epidemics, and pandemics.

A framework for evaluating the effects of observational type and quality on vector-borne disease forecast

Recent research has advanced infectious disease forecasting from an aspiration to an operational reality. The accuracy of such operational forecasting depends on the quantity and quality of observations available for system optimization. In particular, for forecasting systems that use combined mechanistic model-inference approaches, a broad suite of epidemiological observations could be utilized, if these data were available in near real time. In cases where such data are limited, an in silica, synthetic framework for evaluating the potential benefits of observations on forecasting accuracy can allow researchers and public health officials to more optimally allocate resources for disease surveillance and monitoring. Here, we demonstrate the application of such a framework, using a model-inference system designed to predict dengue, and identify the type and quality of observations that would improve forecasting accuracy.

Low to medium-low risk perception for dengue, chikungunya and Zika outbreaks by infectious diseases physicians in France, Western Europe

Background

Many tropical countries are currently experiencing dengue (DEN), chikungunya (CHIK) and also more recently Zika (ZIKA) epidemics (particularly in Latin America). Although the risk of transmission and spread of these infections in temperate regions remains a controversial issue, vector-borne diseases have been widely reported in the media and have been the focus of preventive strategies by national and international policy-makers and public health authorities. In this context, we wanted to determine the extent of risk perception in infectious diseases (ID) physicians of the current and future risk of arboviral disease introduction, autochthonous case development and epidemic scenarios in France, Western Europe.

Methods

To this aim, we developed an original standardized questionnaire survey which was disseminated by the French Infectious Diseases Society to ID physician members.

Results

We found that ID physicians perceived the risk of introduction and outbreak development of DEN, CHIK and ZIKA in France to be low to medium-low. Generalized Linear Model(s) identified medical school training, the extent of professional experience, and awareness of the French national plan regarding arboviral infections as significant predictors for lower risk perception among respondents.

Conclusion

Despite the fact that arboviral diseases are increasingly being imported into France, sometimes resulting in sporadic autochtonous transmission, French ID physicians do not perceive the risk as high. Better communication and education targeting health professionals and citizens will be needed to enhance the effectiveness of the French national plan to prepare against arboviral diseases.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-7317-9) contains supplementary material, which is available to authorized users.

Zika Virus and Future Research Directions

There was a dramatic upsurge in research activity after the recognition of Zika virus (ZIKV) transmission in South America in 2015 and its causal relationship to devastating anomalies in newborn infants. Progress in this area required a community of arbovirologists poised to refocus their research efforts and rapidly characterize the features of ZIKV transmission and infection through diverse multidisciplinary collaborations. Significant gaps remain in our knowledge of the natural history of ZIKV infection, its effects on neurodevelopment, modes and risk of transmission, and its interrelationship with other arbovirus infections. Development of effective countermeasures, such as therapeutics and an effective vaccine, are also research priorities. Lessons learned from our research response to ZIKV may help public health officials plan for the next emerging infectious disease threat.The last 18 months have witnessed one of the most rapid and coordinated research responses against an emerging disease to date. Zika virus, a pathogen that has been known since 1947 but poorly studied until recently because it was believed to only cause a mild infection, has rapidly become the object of intense investigation by the international research community since the link between infection and severe congenital disease was announced by Brazilian authorities in November 2015. According to PubMed, the total number of ZIKV-related publications skyrocketed from 117 in 2015 to 3253 in August of 2017. This supplement summarizes the tremendous progress that has been made since 2015 to elucidate the biology of this virus, its various disease manifestations in humans and animals, the diverse routes by which it is transmitted, and the role of various mosquito vectors in the recent outbreaks. In addition, several efforts have been initiated to develop new diagnostics, therapeutics, vaccines, and vector control strategies to better detect, treat, and prevent this important infection. There are 3 factors that contributed to the rapid progress in ZIKV research: (1) the availability of dedicated funding for ZIKV research; (2) the prior existence of both flavivirologists and maternal-child health researchers who were poised to tackle this new public health challenge; and (3) the high level of coordination and collaboration between different research agencies worldwide.Despite the significant progress, many significant questions remain to be addressed to accelerate the development of effective ZIKV countermeasures and increase our preparedness against this significant public health threat. Some of the most pressing scientific gaps that need to be addressed to advance the field are summarized below.

Development and Validation of Reverse Transcription Loop-Mediated Isothermal Amplification (RT-LAMP) for Rapid Detection of ZIKV in Mosquito Samples from Brazil

The rapid spread of Zika virus (ZIKV) represents a global public health problem, especially in areas that harbor several mosquito species responsible for virus transmission, such as Brazil. In these areas, improvement in mosquito control needs to be a top priority, but mosquito viral surveillance occurs inefficiently in ZIKV-endemic countries. Quantitative reverse transcription PCR (qRT-PCR) is the gold standard for molecular diagnostic of ZIKV in both human and mosquito samples. However, the technique presents high cost and limitations for Point-of-care (POC) diagnostics, which hampers its application for a large number of samples in entomological surveillance programs. Here, we developed and validated a one-step reverse transcription LAMP (RT-LAMP) platform for detection of ZIKV in mosquito samples. The RT-LAMP assay was highly specific for ZIKV and up to 10,000 times more sensitive than qRT-PCR. Assay validation was performed using 60 samples from Aedes aegypti and Culex quinquefasciatus mosquitoes collected in Pernambuco State, Brazil, which is at the epicenter of the Zika epidemic. The RT-LAMP had a sensitivity of 100%, specificity of 91.18%, and overall accuracy of 95.24%. Thus, our POC diagnostics is a powerful and inexpensive tool to monitor ZIKV in mosquito populations and will allow developing countries to establish better control strategies for this devastating pathogen.

Mathematical Modeling and Characterization of the Spread of Chikungunya in Colombia

The Chikungunya virus is the cause of an emerging disease in Asia and Africa, and also in America, where the virus was first detected in 2006. In this paper, we present a mathematical model of the Chikungunya epidemic at the population level that incorporates the transmission vector. The epidemic threshold parameter R 0 for the extinction of disease is computed using the method of the next generation matrix, which allows for insights about what are the most relevant model parameters. Using Lyapunov function theory, some sufficient conditions for global stability of the the disease-free equilibrium are obtained. The proposed mathematical model of the Chikungunya epidemic is used to investigate and understand the importance of some specific model parameters and to give some explanation and understanding about the real infected cases with Chikungunya virus in Colombia for data belonging to the year 2015. In this study, we were able to estimate the value of the basic reproduction number R 0 . We use bootstrapping and Markov chain Monte Carlo techniques in order to study parameters’ identifiability. Finally, important policies and insights are provided that could help government health institutions in reducing the number of cases of Chikungunya in Colombia.

Zika outbreak aftermath: status, progress, concerns and new insights

Zika, a neurotrophic virus belonging to Flaviviridae family of viruses and transmitted by vector mosquitoes of Aedes species, took the world by storm during its recent outbreak. Its spread to newer territories, unprecedented pace of transmission, lack of existing therapeutic agents and vaccines and an empty drug pipeline raised an alarm. Uncertainty about full spectrum of diseases and its long-term consequences, newly discovered modes of transmission and controversies over vector status of mosquito species like Culex quinquefasciatus led to layers of complexity and presented new hurdles and challenges in Zika virus research. This review summarizes the progress and updates of efforts, concerns, financial burden and available resources in light of newly acquired knowledge in Zika virus research.

Modeling the importation and local transmission of vector-borne diseases in Florida: The case of Zika outbreak in 2016

Chikungunya, dengue, and Zika viruses are all transmitted by Aedes aegypti and Aedes albopictus mosquito species, had been imported to Florida and caused local outbreaks. We propose a deterministic model to study the importation and local transmission of these mosquito-borne diseases. The purpose is to model and mimic the importation of these viruses to Florida via travelers, local infections in domestic mosquitoes by imported travelers, and finally non-travel related transmissions to local humans by infected local mosquitoes. As a case study, the model will be used to simulate the accumulative Zika cases in Florida. Since the disease system is driven by a continuing input of infections from outside sources, orthodox analytic methods based on the calculation of the basic reproduction number are inadequate to describe and predict their behavior. Via steady-state analysis and sensitivity analysis, effective control and prevention measures for these mosquito-borne diseases are tested.

Human movement, cooperation and the effectiveness of coordinated vector control strategies

Vector-borne disease transmission is often typified by highly focal transmission and influenced by movement of hosts and vectors across different scales. The ecological and environmental conditions (including those created by humans through vector control programmes) that result in metapopulation dynamics remain poorly understood. The development of control strategies that would most effectively limit outbreaks given such dynamics is particularly urgent given the recent epidemics of dengue, chikungunya and Zika viruses. We developed a stochastic, spatial model of vector-borne disease transmission, allowing for movement of hosts between patches. Our model is applicable to arbovirus transmission by Aedes aegypti in urban settings and was parametrized to capture Zika virus transmission in particular. Using simulations, we investigated the extent to which two aspects of vector control strategies are affected by human commuting patterns: the extent of coordination and cooperation between neighbouring communities. We find that transmission intensity is highest at intermediate levels of host movement. The extent to which coordination of control activities among neighbouring patches decreases the prevalence of infection is affected by both how frequently humans commute and the proportion of neighbouring patches that commits to vector surveillance and control activities. At high levels of host movement, patches that do not contribute to vector control may act as sources of infection in the landscape, yet have comparable levels of prevalence as patches that do cooperate. This result suggests that real cooperation among neighbours will be critical to the development of effective pro-active strategies for vector-borne disease control in today's commuter-linked communities.

Primary blood-hosts of mosquitoes are influenced by social and ecological conditions in a complex urban landscape

Background

Temperate urban landscapes support persistent and growing populations of Culex and Aedes mosquito vectors. Large urban mosquito populations can represent a significant risk for transmission of emergent arboviral infection. However, even large mosquito populations are only a risk to the animals they bite. The purpose of this study is to identify and assess spatial patterns of host-use in a temperate urban landscape with heterogeneous socio-economic and ecological conditions.

Results

Mosquito blood meals were collected from neighborhoods categorized along a socio-economic gradient in Baltimore, MD, USA. Blood meal hosts were identified for two Aedes (Ae. albopictus and Ae. japonicus) and three Culex (Cx. pipiens, Cx. restuans and Cx. salinarius) species. The brown rat (Rattus norvegicus) was the most frequently detected host in both Aedes species and Cx. salinarius. Human biting was evident in Aedes and Culex species and the proportion of human blood meals from Ae. albopictus varied significantly with neighborhood socio-economic status. Aedes albopictus was most likely to feed on human blood hosts (at 50%) in residential blocks categorized as having income above the city median, although there were still more total human bites detected from lower income blocks where Ae. albopictus was more abundant. Birds were the most frequently detected Culex blood hosts but were absent from all Aedes sampled.

Conclusions

This study highlights fine-scale variation in host-use by medically important mosquito vectors and specifically investigates blood meal composition at spatial scales relevant to urban mosquito dispersal and human exposure. Further, the work emphasizes the importance of neighborhood economics and infrastructure management in shaping both the relative abundance of vectors and local blood feeding strategies. The invasive brown rat was an important blood source across vector species and neighborhoods in Baltimore. We show that social and economic conditions can be important predictors of transmission potential in urban landscapes and identify important questions about the role of rodents in supporting urban mosquito populations.

Consensus and conflict among ecological forecasts of Zika virus outbreaks in the United States

Ecologists are increasingly involved in the pandemic prediction process. In the course of the Zika outbreak in the Americas, several ecological models were developed to forecast the potential global distribution of the disease. Conflicting results produced by alternative methods are unresolved, hindering the development of appropriate public health forecasts. We compare ecological niche models and experimentally-driven mechanistic forecasts for Zika transmission in the continental United States. We use generic and uninformed stochastic county-level simulations to demonstrate the downstream epidemiological consequences of conflict among ecological models, and show how assumptions and parameterization in the ecological and epidemiological models propagate uncertainty and produce downstream model conflict. We conclude by proposing a basic consensus method that could resolve conflicting models of potential outbreak geography and seasonality. Our results illustrate the usually-undocumented margin of uncertainty that could emerge from using any one of these predictions without reservation or qualification. In the short term, ecologists face the task of developing better post hoc consensus that accurately forecasts spatial patterns of Zika virus outbreaks. Ultimately, methods are needed that bridge the gap between ecological and epidemiological approaches to predicting transmission and realistically capture both outbreak size and geography.

Profile likelihood-based analyses of infectious disease models

Ordinary differential equation models are frequently applied to describe the temporal evolution of epidemics. However, ordinary differential equation models are also utilized in other scientific fields. We summarize and transfer state-of-the art approaches from other fields like Systems Biology to infectious disease models. For this purpose, we use a simple SIR model with data from an influenza outbreak at an English boarding school in 1978 and a more complex model of a vector-borne disease with data from the Zika virus outbreak in Colombia in 2015-2016. Besides parameter estimation using a deterministic multistart optimization approach, a multitude of analyses based on the profile likelihood are presented comprising identifiability analysis and model reduction. The analyses were performed using the freely available modeling framework Data2Dynamics (data2dynamics.org) which has been awarded as best performing within the DREAM6 parameter estimation challenge and in the DREAM7 network reconstruction challenge.

Inferring the risk factors behind the geographical spread and transmission of Zika in the Americas

BACKGROUND

An unprecedented Zika virus epidemic occurred in the Americas during 2015-2016. The size of the epidemic in conjunction with newly recognized health risks associated with the virus attracted significant attention across the research community. Our study complements several recent studies which have mapped epidemiological elements of Zika, by introducing a newly proposed methodology to simultaneously estimate the contribution of various risk factors for geographic spread resulting in local transmission and to compute the risk of spread (or re-introductions) between each pair of regions. The focus of our analysis is on the Americas, where the set of regions includes all countries, overseas territories, and the states of the US.

METHODOLOGY/PRINCIPAL FINDINGS

We present a novel application of the Generalized Inverse Infection Model (GIIM). The GIIM model uses real observations from the outbreak and seeks to estimate the risk factors driving transmission. The observations are derived from the dates of reported local transmission of Zika virus in each region, the network structure is defined by the passenger air travel movements between all pairs of regions, and the risk factors considered include regional socioeconomic factors, vector habitat suitability, travel volumes, and epidemiological data. The GIIM relies on a multi-agent based optimization method to estimate the parameters, and utilizes a data driven stochastic-dynamic epidemic model for evaluation. As expected, we found that mosquito abundance, incidence rate at the origin region, and human population density are risk factors for Zika virus transmission and spread. Surprisingly, air passenger volume was less impactful, and the most significant factor was (a negative relationship with) the regional gross domestic product (GDP) per capita.

CONCLUSIONS/SIGNIFICANCE

Our model generates country level exportation and importation risk profiles over the course of the epidemic and provides quantitative estimates for the likelihood of introduced Zika virus resulting in local transmission, between all origin-destination travel pairs in the Americas. Our findings indicate that local vector control, rather than travel restrictions, will be more effective at reducing the risks of Zika virus transmission and establishment. Moreover, the inverse relationship between Zika virus transmission and GDP suggests that Zika cases are more likely to occur in regions where people cannot afford to protect themselves from mosquitoes. The modeling framework is not specific for Zika virus, and could easily be employed for other vector-borne pathogens with sufficient epidemiological and entomological data.

The importance of being urgent: The impact of surveillance target and scale on mosquito-borne disease control

With the emergence or re-emergence of numerous mosquito-borne diseases in recent years, effective methods for emergency vector control responses are necessary to reduce human infections. Current vector control practices often vary significantly between different jurisdictions, and are executed independently and at different spatial scales. Various types of surveillance information (e.g. number of human infections or adult mosquitoes) trigger the implementation of control measures, though the target and scale of surveillance vary locally. This patchy implementation of control measures likely alters the efficacy of control. We modeled six different scenarios, with larval mosquito control occurring in response to surveillance data of different types and at different scales (e.g. across the landscape or in each patch). Our results indicate that: earlier application of larvicide after an escalation of disease risk achieves much greater reductions in human infections than later control implementation; uniform control across the landscape provides better outbreak mitigation than patchy control application; and different types of surveillance data require different levels of sensitivity in their collection to effectively inform control measures. Our simulations also demonstrate a potential logical fallacy of reactive, surveillance-driven vector control: measures stop being implemented as soon as they are deemed effective. This false sense of security leads to patchier control efforts that will do little to curb the size of future vector-borne disease outbreaks. More investment should be placed in collecting high quality information that can trigger early and uniform implementation, while researchers work to discover more informative metrics of human risk to trigger more effective control.

Quantifying Zika: Advancing the Epidemiology of Zika With Quantitative Models

When Zika virus (ZIKV) emerged in the Americas, little was known about its biology, pathogenesis, and transmission potential, and the scope of the epidemic was largely hidden, owing to generally mild infections and no established surveillance systems. Surges in congenital defects and Guillain-Barré syndrome alerted the world to the danger of ZIKV. In the context of limited data, quantitative models were critical in reducing uncertainties and guiding the global ZIKV response. Here, we review some of the models used to assess the risk of ZIKV-associated severe outcomes, the potential speed and size of ZIKV epidemics, and the geographic distribution of ZIKV risk. These models provide important insights and highlight significant unresolved questions related to ZIKV and other emerging pathogens.

A survey-based study of Zika virus communication preferences among pregnant women in Georgia, United States

BACKGROUND

Because of the particularly severe perinatal outcomes associated with antenatal Zika virus infection, it is important for prenatal care providers to communicate Zika virus risks and strategies for prevention to their patients. Although face-to-face communication is ideal, clinic visits may not allow for in-depth discussion of all concerns. While previous studies have shown prenatal providers to be pregnant women's most trusted sources of health information, there is little knowledge on what secondary communication modalities pregnant women prefer for receiving information from their providers about an evolving public health emergency.

METHODS

A cross-sectional, descriptive anonymous 27-item survey was distributed to pregnant women at four clinics around Atlanta, Georgia from May 5th to June 20th, 2016. The survey assessed women's interest in and communication preferences about prenatal topics, including Zika virus. Descriptive statistics were calculated and chi-square tests were used to evaluate associations between the primary outcomes and patient characteristics.

RESULTS

Four-hundred and eight women completed the survey. The most popular resource for obtaining Zika virus information was the Centers for Disease Control and Prevention (CDC) website (73.0%). While their prenatal provider's own website for Zika information ranked 5th among sources currently accessed for Zika information, it ranked third behind educational brochures and emails for ways in which women wanted to receive information. The characteristics of Zika virus information deemed most important were: evidence-based (87.5%), endorsed by the CDC (74.1%), and endorsed by their own provider (67.9%).

CONCLUSION

In any public health emergency affecting pregnant women, women are going to seek advice from their obstetric providers. Because providers may lack sufficient time to discuss concerns with every patient, they may consider providing patient education in other ways. For the women included in this study, educational brochures, emails and providers' own practice websites were preferred. Providers should consider taking greater advantage of these modalities to supplement in-person exchanges, particularly during a public health emergency.

The risk of sustained sexual transmission of Zika is underestimated

Pathogens often follow more than one transmission route during outbreaks-from needle sharing plus sexual transmission of HIV to small droplet aerosol plus fomite transmission of influenza. Thus, controlling an infectious disease outbreak often requires characterizing the risk associated with multiple mechanisms of transmission. For example, during the Ebola virus outbreak in West Africa, weighing the relative importance of funeral versus health care worker transmission was essential to stopping disease spread. As a result, strategic policy decisions regarding interventions must rely on accurately characterizing risks associated with multiple transmission routes. The ongoing Zika virus (ZIKV) outbreak challenges our conventional methodologies for translating case-counts into route-specific transmission risk. Critically, most approaches will fail to accurately estimate the risk of sustained sexual transmission of a pathogen that is primarily vectored by a mosquito-such as the risk of sustained sexual transmission of ZIKV. By computationally investigating a novel mathematical approach for multi-route pathogens, our results suggest that previous epidemic threshold estimates could under-estimate the risk of sustained sexual transmission by at least an order of magnitude. This result, coupled with emerging clinical, epidemiological, and experimental evidence for an increased risk of sexual transmission, would strongly support recent calls to classify ZIKV as a sexually transmitted infection.

Socio-Ecological Mechanisms Supporting High Densities of Aedes albopictus (Diptera: Culicidae) in Baltimore, MD

Social, ecological, and climatic factors interact creating a heterogeneous matrix that determines the spatiotemporal distribution of mosquitoes and human risks of exposure to the diseases they transmit. We explore linkages between the social and institutional processes behind residential abandonment, urban ecology, and the interactions of socio-ecological processes with abiotic drivers of mosquito production. Specifically, we test the relative roles of infrastructure degradation and vegetation for explaining the presence of Aedes albopictus Skuse 1894 to better predict spatial heterogeneity in mosquito exposure risk within urban environments. We further examine how precipitation interacts with these socially underpinned biophysical variables. We use a hierarchical statistical modeling approach to assess how environmental and climatic conditions over 3 years influence mosquito ecology across a socioeconomic gradient in Baltimore, MD. We show that decaying infrastructure and vegetation are important determinants of Ae. albopictus infestation. We demonstrate that both precipitation and vegetation influence mosquito production in ways that are mediated by the level of infrastructural decay on a given block. Mosquitoes were more common on blocks with greater abandonment, but when precipitation was low, mosquitoes were more likely to be found in higher-income neighborhoods with managed container habitat. Likewise, although increased vegetation was a negative predictor of mosquito infestation, more vegetation on blocks with high abandonment was associated with the largest mosquito populations. These findings indicate that fine spatial scale modeling of mosquito habitat within urban areas is needed to more accurately target vector control.

Citizen Science as a Tool for Mosquito Control

In this paper, we share our findings from a 2-year citizen science program called Mosquito Stoppers. This pest-oriented citizen science project is part of a larger coupled natural-human systems project seeking to understand the fundamental drivers of mosquito population density and spatial variability in potential exposure to mosquito-borne pathogens in a matrix of human construction, urban renewal, and individual behaviors. Focusing on residents in West Baltimore, participants were recruited through neighborhood workshops and festivals. Citizen scientists participated in yard surveys of potential mosquito habitat and in evaluating mosquito nuisance. We found that citizen scientists, with minimal education and training, were able to accurately collect data that reflect trends found in a comparable researcher-generated database.

Local environmental and meteorological conditions influencing the invasive mosquito Ae. albopictus and arbovirus transmission risk in New York City

Ae. albopictus, an invasive mosquito vector now endemic to much of the northeastern US, is a significant public health threat both as a nuisance biter and vector of disease (e.g. chikungunya virus). Here, we aim to quantify the relationships between local environmental and meteorological conditions and the abundance of Ae. albopictus mosquitoes in New York City. Using statistical modeling, we create a fine-scale spatially explicit risk map of Ae. albopictus abundance and validate the accuracy of spatiotemporal model predictions using observational data from 2016. We find that the spatial variability of annual Ae. albopictus abundance is greater than its temporal variability in New York City but that both local environmental and meteorological conditions are associated with Ae. albopictus numbers. Specifically, key land use characteristics, including open spaces, residential areas, and vacant lots, and spring and early summer meteorological conditions are associated with annual Ae. albopictus abundance. In addition, we investigate the distribution of imported chikungunya cases during 2014 and use these data to delineate areas with the highest rates of arboviral importation. We show that the spatial distribution of imported arboviral cases has been mostly discordant with mosquito production and thus, to date, has provided a check on local arboviral transmission in New York City. We do, however, find concordant areas where high Ae. albopictus abundance and chikungunya importation co-occur. Public health and vector control officials should prioritize control efforts to these areas and thus more cost effectively reduce the risk of local arboviral transmission. The methods applied here can be used to monitor and identify areas of risk for other imported vector-borne diseases.

Opportunities and challenges in modeling emerging infectious diseases

The term "pathogen emergence" encompasses everything from previously unidentified viruses entering the human population to established pathogens invading new populations and the evolution of drug resistance. Mathematical models of emergent pathogens allow forecasts of case numbers, investigation of transmission mechanisms, and evaluation of control options. Yet, there are numerous limitations and pitfalls to their use, often driven by data scarcity. Growing availability of data on pathogen genetics and human ecology, coupled with computational and methodological innovations, is amplifying the power of models to inform the public health response to emergence events. Tighter integration of infectious disease models with public health practice and development of resources at the ready has the potential to increase the timeliness and quality of responses.

Pokémon Go and Exposure to Mosquito-Borne Diseases: How Not to Catch 'Em All

Pokémon Go is a new game that encourages players to venture outdoors and interact with others in the pursuit of virtual Pokémon characters. With more time spent outdoors overall and in sometimes large congregations, Pokémon Go players could inadvertently elevate their risk of exposure to mosquito-borne diseases when playing in certain areas at certain times of year. Here, we make an initial assessment of the possible scope of this concern in the continental United States, which experiences its highest seasonal transmission of West Nile, Zika, and other viruses during summer and early fall. In particular, we propose that the times of day when many disease-relevant mosquito species are most likely to engage in blood feeding coincide with times of day when Pokémon Go activity is likely to be high, and we note that locations serving as hubs of Pokémon Go activity may in some cases overlap with areas where these mosquitoes are actively engaged in blood feeding. Although the risk of mosquito-borne diseases in the continental U.S. is low overall and is unlikely to be impacted significantly by Pokémon Go, it is nonetheless important for Pokémon Go players and others who spend time outdoors engaging in activities such as barbecues and gardening to be aware of these ongoing risks and to take appropriate preventative measures in light of the potential for outdoor activity to modify individual-level risk of exposure. As Pokémon Go and other augmented reality games become available in other parts of the world, similar risks should be assessed in a manner that is consistent with the local epidemiology of mosquito-borne diseases in those areas.