Mapping global environmental suitability for Zika virus

Approaches and perspectives for online learning during the COVID-19 pandemic and future chaos

BACKGROUND

Online learning (OLL) methodology has been incorporated in higher education extensively on the mount over the last few decades and with the onset of COVID-19 situation, the virtual method in academia became essential. After observing worldly destructions and death due to coronavirus, the WHO declared a high alert emergency, and since Pakistan started to follow lockdown since March 2020 to prevent high penetration and consequently, the online teaching method was adapted to keep the learning atmosphere alive. The study is aimed to identify the influencing factors and compliance for the implementation of the OLL system in COVID-19 and, in the future, nonpandemic state as well.

MATERIALS AND METHODS

The present study is designed to observe the adaptability and hurdles among pharmacy students, and for the purpose of the study, a questionnaire on the Likert scale was developed and asked to respond from pharmacy undergraduate and postgraduate students after taking consensus, which further analyzed through IBM SPSS Statistics Version 26.

RESULTS

The outcomes of the study were analyzed with a high level of conformity; however, the gender-based reservations were observed, and moreover, merits of OLL were observed with high jeopardy.

CONCLUSION

The adaptation of OLL, though proved as the only troubleshooter in an uncontrollable situation and enabled universities, professors, and students for patience, resilience, and hopefully, will serve as swift safeguard for future challenges of epidemic and pandemic disasters. According to the evolution theory, brain adaptability and plasticity of human organisms grow the capacity to adjust itself with an advanced characteristic.

Ecology, evolution, and epidemiology of zoonotic and vector-borne infectious diseases in French Guiana: Transdisciplinarity does matter to tackle new emerging threats

French Guiana is a European ultraperipheric region located on the northern Atlantic coast of South America. It constitutes an important forested region for biological conservation in the Neotropics. Although very sparsely populated, with its inhabitants mainly concentrated on the Atlantic coastal strip and along the two main rivers, it is marked by the presence and development of old and new epidemic disease outbreaks, both research and health priorities. In this review paper, we synthetize 15 years of multidisciplinary and integrative research at the interface between wildlife, ecosystem modification, human activities and sociodemographic development, and human health. This study reveals a complex epidemiological landscape marked by important transitional changes, facilitated by increased interconnections between wildlife, land-use change and human occupation and activity, human and trade transportation, demography with substantial immigration, and identified vector and parasite pharmacological resistance. Among other French Guianese characteristics, we demonstrate herein the existence of more complex multi-host disease life cycles than previously described for several disease systems in Central and South America, which clearly indicates that today the greater promiscuity between wildlife and humans due to demographic and economic pressures may offer novel settings for microbes and their hosts to circulate and spread. French Guiana is a microcosm that crystallizes all the current global environmental, demographic and socioeconomic change conditions, which may favor the development of ancient and future infectious diseases.

Lying in wait: the resurgence of dengue virus after the Zika epidemic in Brazil

After the Zika virus (ZIKV) epidemic in the Americas in 2016, both Zika and dengue incidence declined to record lows in many countries in 2017–2018, but in 2019 dengue resurged in Brazil, causing ~2.1 million cases. In this study we use epidemiological, climatological and genomic data to investigate dengue dynamics in recent years in Brazil. First, we estimate dengue virus force of infection (FOI) and model mosquito-borne transmission suitability since the early 2000s. Our estimates reveal that DENV transmission was low in 2017–2018, despite conditions being suitable for viral spread. Our study also shows a marked decline in dengue susceptibility between 2002 and 2019, which could explain the synchronous decline of dengue in the country, partially as a result of protective immunity from prior ZIKV and/or DENV infections. Furthermore, we performed phylogeographic analyses using 69 newly sequenced genomes of dengue virus serotype 1 and 2 from Brazil, and found that the outbreaks in 2018–2019 were caused by local DENV lineages that persisted for 5–10 years, circulating cryptically before and after the Zika epidemic. We hypothesize that DENV lineages may circulate at low transmission levels for many years, until local conditions are suitable for higher transmission, when they cause major outbreaks.

Zika and dengue incidence in the Americas declined in 2017–2018, but dengue resurged in 2019 in Brazil. This study uses epidemiological, climatological and genomic data to show that the decline of dengue may be explained by protective immunity from pre-exposure to ZIKV and/or DENV in prior years.

Is the ZIKV Congenital Syndrome and Microcephaly Due to Syndemism with Latent Virus Coinfection?

The emergence of the Zika virus (ZIKV) mirrors its evolutionary nature and, thus, its ability to grow in diversity or complexity (i.e., related to genome, host response, environment changes, tropism, and pathogenicity), leading to it recently joining the circle of closed congenital pathogens. The causal relation of ZIKV to microcephaly is still a much-debated issue. The identification of outbreak foci being in certain endemic urban areas characterized by a high-density population emphasizes that mixed infections might spearhead the recent appearance of a wide range of diseases that were initially attributed to ZIKV. Globally, such coinfections may have both positive and negative effects on viral replication, tropism, host response, and the viral genome. In other words, the possibility of coinfection may necessitate revisiting what is considered to be known regarding the pathogenesis and epidemiology of ZIKV diseases. ZIKV viral coinfections are already being reported with other arboviruses (e.g., chikungunya virus (CHIKV) and dengue virus (DENV)) as well as congenital pathogens (e.g., human immunodeficiency virus (HIV) and cytomegalovirus (HCMV)). However, descriptions of human latent viruses and their impacts on ZIKV disease outcomes in hosts are currently lacking. This review proposes to select some interesting human latent viruses (i.e., herpes simplex virus 2 (HSV-2), Epstein-Barr virus (EBV), human herpesvirus 6 (HHV-6), human parvovirus B19 (B19V), and human papillomavirus (HPV)), whose virological features and co-exposition with ZIKV may provide evidence of the syndemism process, shedding some light on the emergence of the ZIKV-induced global congenital syndrome in South America.

Spatiotemporal patterns and spatial risk factors for visceral leishmaniasis from 2007 to 2017 in Western and Central China: A modelling analysis

Visceral leishmaniasis (VL) is a neglected disease caused by trypanosomatid protozoa in the genus Leishmania, which is transmitted by phlebotomine sandflies. Although this vector-borne disease has been eliminated in several regions of China during the last century, the reported human VL cases have rebounded in Western and Central China in recent decades. However, understanding of the spatial epidemiology of the disease remains vague, as the spatial risk factors driving the spatial heterogeneity of VL. In this study, we analyzed the spatiotemporal patterns of annual human VL cases in Western and Central China from 2007 to 2017. Based on the related spatial maps, the boosted regression tree (BRT) model was adopted to explore the relationships between VL and spatial correlates as well as predicting both the existing and potential infection risk zones of VL in Western and Central China. The mined links reveal that elevation, minimum temperature, relative humidity, and annual accumulated precipitation make great contributions to the spatial heterogeneity of VL. The maps show that Xinjiang Uygur Autonomous Region, Gansu, western Inner Mongolia Autonomous Region, and Sichuan are predicted to fall in the highest infection risk zones of VL. Approximately 61.60 million resident populations lived in the high-risk regions of VL in Western and Central China. Our results provide a better understanding of how spatial risk factors driving VL spread as well as identifying the potential endemic risk region of VL, thereby enhancing the biosurveillance capacity of public health authorities.

COVID-19, Chikungunya, Dengue and Zika Diseases: An Analytical Platform Based on MALDI-TOF MS, IR Spectroscopy and RT-qPCR for Accurate Diagnosis and Accelerate Epidemics Control

COVID-19 and arboviruses (ARBOD) epidemics co-occurrence is a great concern. In tropical and subtropical regions, ARBOD diseases such as chikungunya, dengue, and Zika are frequent. In both COVID-19 and ARBOD cases, an accurate diagnosis of infected patients is crucial to promote adequate treatment and isolation measures in COVID-19 cases. Overlap of clinical symptoms and laboratory parameters between COVID-19 and ARBOD present themselves as an extra challenge during diagnosis. COVID-19 diagnosis is mainly performed by quantitative reverse polymerase chain reaction (RT-qPCR), while ARBOD diagnosis is performed by serology, detection of antigen or antibody, and molecular diagnosis. In this review, the epidemiologic profile of arboviruses and SARS-CoV-2 is analyzed, and potential risks of symptom overlap is addressed. The implementation of an analytical platform based on infrared (IR) spectroscopy, MALDI-TOF mass spectrometry, and RT-qPCR is discussed as an efficient strategy for a fast, robust, reliable, and cost-effective diagnosis system even during the co-occurrence of virus outbreaks. The spectral data of IR spectroscopy and MALDI-TOF MS obtained from COVID-19 infected and recovered patients can be used to build up an integrated spectral database. This approach can enable us to determine quickly the groups that have been exposed and have recovered from COVID-19 or ARBOD, avoiding misdiagnoses.

Genomic and Epidemiological Surveillance of Zika Virus in the Amazon Region

Zika virus (ZIKV) has caused an explosive epidemic linked to severe clinical outcomes in the Americas. As of June 2018, 4,929 ZIKV suspected infections and 46 congenital syndrome cases had been reported in Manaus, Amazonas, Brazil. Although Manaus is a key demographic hub in the Amazon region, little is known about the ZIKV epidemic there, in terms of both transmission and viral genetic diversity. Using portable virus genome sequencing, we generated 59 ZIKV genomes in Manaus. Phylogenetic analyses indicated multiple introductions of ZIKV from northeastern Brazil to Manaus. Spatial genomic analysis of virus movement among six areas in Manaus suggested that populous northern neighborhoods acted as sources of virus transmission to other neighborhoods. Our study revealed how the ZIKV epidemic was ignited and maintained within the largest urban metropolis in the Amazon. These results might contribute to improving the public health response to outbreaks in Brazil.

Measuring the global burden of chikungunya and Zika viruses: A systematic review

Throughout the last decade, chikungunya virus (CHIKV) and Zika virus (ZIKV) infections have spread globally, causing a spectrum of disease that ranges from self-limited febrile illness to permanent severe disability, congenital anomalies, and early death. Nevertheless, estimates of their aggregate health impact are absent from the literature and are currently omitted from the Global Burden of Disease (GBD) reports. We systematically reviewed published literature and surveillance records to evaluate the global burden caused by CHIKV and ZIKV between 2010 and 2019, to calculate estimates of their disability-adjusted life year (DALY) impact. Extracted data on acute, chronic, and perinatal outcomes were used to create annualized DALY estimates, following techniques outlined in the GBD framework. This study is registered with PROSPERO (CRD42020192502). Of 7,877 studies identified, 916 were screened in detail, and 21 were selected for inclusion. Available data indicate that CHIKV and ZIKV caused the average yearly loss of over 106,000 and 44,000 DALYs, respectively, between 2010 and 2019. Both viruses caused substantially more burden in the Americas than in any other World Health Organization (WHO) region. This unequal distribution is likely due to a combination of limited active surveillance reporting in other regions and the lack of immunity that left the previously unexposed populations of the Americas susceptible to severe outbreaks during the last decade. Long-term rheumatic sequelae provided the largest DALY component for CHIKV, whereas congenital Zika syndrome (CZS) contributed most significantly for ZIKV. Acute symptoms and early mortality accounted for relatively less of the overall burden. Suboptimal reporting and inconsistent diagnostics limit precision when determining arbovirus incidence and frequency of complications. Despite these limitations, it is clear from our assessment that CHIKV and ZIKV represent a significant cause of morbidity that is not included in current disease burden reports. These results suggest that transmission-blocking strategies, including vector control and vaccine development, remain crucial priorities in reducing global disease burden through prevention of potentially devastating arboviral outbreaks.

Chikungunya and Zika are 2 mosquito-borne viral diseases that can cause both acute symptoms and long-term, debilitating complications in infected individuals. Chikungunya is best known as a cause of persistent arthritis in otherwise recovered patients and Zika as a cause of cognitive, motor, and sensory anomalies in newborn children. Both diseases emerged in the Americas within the last decade and have since spread rapidly throughout the region. Despite their widespread transmission there and throughout much of the world, chikungunya and Zika remain neglected diseases. One of the most significant obstacles to address their spread is a lack of data involving their burden. We searched the published literature and surveillance reports to collect information about the incidence, mortality, and morbidity associated with each of these diseases to estimate their regional and global burden during the last decade. Our estimates confirm that chikungunya and Zika caused substantial burden throughout this time frame and place them among the most problematic mosquito-borne viral diseases worldwide. We found that the largest proportion of global burden linked to each disease between 2010 and 2019 occurred in the Americas, although this observation is likely due to limited reporting in other regions.

Modeling dengue vector population with earth observation data and a generalized linear model

Mosquitoes propagate many human diseases, some widespread and with no vaccines. The Ae. aegypti mosquito vector transmits Zika, Chikungunya, and Dengue viruses. Effective public health interventions to control the spread of these diseases and protect the population require models that explain the core environmental drivers of the vector population. Field campaigns are expensive, and data from meteorological sites that feed models with the required environmental data often lack detail. As a consequence, we explore temporal modeling of the population of Ae. aegypti mosquito vector species and environmental conditions- temperature, moisture, precipitation, and vegetation- have been shown to have significant effects. We use earth observation (EO) data as our source for estimating these biotic and abiotic environmental variables based on proxy features, namely: Normalized difference vegetation index, Normalized difference water index, Precipitation, and Land surface temperature. We obtained our response variable from field-collected mosquito population measured weekly using 791 mosquito traps in Vila Velha city, Brazil, for 36 weeks in 2017, and 40 weeks in 2018. Recent similar studies have used machine learning (ML) techniques for this task. However, these techniques are neither intuitive nor explainable from an operational point of view. As a result, we use a Generalized Linear Model (GLM) to model this relationship due to its fitness for count response variable modeling, its interpretability, and the ability to visualize the confidence intervals for all inferences. Also, to improve our model, we use the Akaike Information Criterion to select the most informative environmental features. Finally, we show how to improve the quality of the model by weighting our GLM. Our resulting weighted GLM compares well in quality with ML techniques: Random Forest and Support Vector Machines. These results provide an advancement with regards to qualitative and explainable epidemiological risk modeling in urban environments.

Influence of Larval Habitat Environmental Characteristics on Culicidae Immature Abundance and Body Size of Adult Aedes aegypti

Aedes aegypti is adapted to live in close association with human dwellings, where it lays eggs in several man-made container types with a broad range of size, shape, and material. Biotic and abiotic conditions of larval habitats determine the abundance and body size of emerging adult mosquitoes. Here, we estimated the predictive potential of physicochemical water variables for Culicidae immature abundance and Ae. aegypti adult body size in four neighborhoods with distinct urban landscapes in Rio de Janeiro, Brazil. Domestic water holding containers (N = 240) were inspected for the presence of Culicidae immatures and had several physiochemical parameters measured. Larvae and pupae were counted, and pupae were reared to the adult stage for taxonomic identification. Dry weight and wing size were measured for Ae. aegypti adult mosquitoes (N = 981). The association between larval habitat parameters with Culicidae abundance and Ae. aegypti body size data was estimated through linear mixed models and generalized linear mixed models, respectively, with the neighborhood as random effect. The abundance of immature Culicidae in larval habitats (from which >90% of adults emerging from field collected pupae were Ae. aegypti) was positively associated with container volume and the dissolved organic carbon concentration (DOC). Female average dry weight and male and female wing lengths were positively associated with larval habitat temperature whereas male average dry weight was positively related to water conductivity. Aedes aegypti originating from larval habitats with Ae. albopictus exhibited no differences in median wing length and dry body weight when compared with specimens collected in containers exclusively colonized by Ae. aegypti. These results demonstrate that container water volume (characteristic easily observed in the field) and DOC (often higher in unmanaged water holding recipients) is related to higher Ae. aegypti immature density. Estimating the effects of physicochemical water variables on immature abundance and adult body size can provide valuable information for predicting arbovirus transmission risk in endemic settings.

Mapping ticks and tick-borne pathogens in China

Understanding ecological niches of major tick species and prevalent tick-borne pathogens is crucial for efficient surveillance and control of tick-borne diseases. Here we provide an up-to-date review on the spatial distributions of ticks and tick-borne pathogens in China. We map at the county level 124 tick species, 103 tick-borne agents, and human cases infected with 29 species (subspecies) of tick-borne pathogens that were reported in China during 1950-2018. Haemaphysalis longicornis is found to harbor the highest variety of tick-borne agents, followed by Ixodes persulcatus, Dermacentor nutalli and Rhipicephalus microplus. Using a machine learning algorithm, we assess ecoclimatic and socioenvironmental drivers for the distributions of 19 predominant vector ticks and two tick-borne pathogens associated with the highest disease burden. The model-predicted suitable habitats for the 19 tick species are 14‒476% larger in size than the geographic areas where these species were detected, indicating severe under-detection. Tick species harboring pathogens of imminent threats to public health should be prioritized for more active field surveillance.

Genome engineering in insects for the control of vector borne diseases

Insects cause many vector-borne infectious diseases and have become a major threat to human health. Although many control measures are undertaken, some insects are resistant to it, exacerbated by environmental changes which is a major challenge for control measures. Genetic studies by targeting the genomes of insects may offer an alternative strategy. Developments with novel genome engineering technologies have stretched our ability to target and modify any genomic sequence in Eukaryotes including insects. Genome engineering tools such as zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and most recently discovered, clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9) systems hold the potential to control the vector-borne diseases. In this chapter, we review the vector control strategy undertaken by employing three major genome engineering tools (ZFNs, TALENs, and CRISPR/Cas9) and discuss the future prospects of this system to control insect vectors. Finally, we also discuss the CRISPR-based gene drive system and its concerns due to ecological impacts.

Differential Longevity of Memory CD4 and CD8 T Cells in a Cohort of the Mothers With a History of ZIKV Infection and Their Children

Background: Zika virus (ZIKV) infection causes for mild and self-limiting disease in healthy adults. In newborns, it can occasionally lead to a spectrum of malformations, the congenital Zika syndrome (CZS). Thus, little is known if mothers and babies with a history of ZIKV infection were able to develop long-lasting T-cell immunity. To these issues, we measure the prevalence of ZIKV T-cell immunity in a cohort of mothers infected to the ZIKV during pregnancy in the 2016–2017 Zika outbreak, who gave birth to infants affected by neurological complications or asymptomatic ones.

Results: Twenty-one mothers and 18 children were tested for IFN-γ ELISpot and T-cell responses for flow cytometry assays in response to CD4 ZIKV and CD8 ZIKV megapools (CD4 ZIKV MP and CD8 ZIKV MP). IFN-γ ELISpot responses to ZIKV MPs showed an increased CD4 and CD8 T-cell responses in mothers compared to children. The degranulation activity and IFN-γ-producing CD4 T cells were detected in most mothers, and children, while in CD8 T-cells, low responses were detected in these study groups. The total Temra T cell subset is enriched for IFN-γ+ CD4 T cells after stimulation of CD4 ZIKV MP.

Conclusion: Donors with a history of ZIKV infection demonstrated long-term CD4 T cell immunity to ZIKV CD4 MP. However, the same was not observed in CD8 T cells with the ZIKV CD8 MP. One possibility is that the cytotoxic and pro-inflammatory activities of CD8 T cells are markedly demonstrated in the early stages of infection, but less detected in the disease resolution phase, when the virus has already been eliminated. The responses of mothers' T cells to ZIKV MPs do not appear to be related to their children's clinical outcome. There was also no marked difference in the T cell responses to ZIKV MP between children affected or not with CZS. These data still need to be investigated, including the evaluation of the response of CD8 T cells to other ZIKV peptides.

A review of models applied to the geographic spread of Zika virus

In recent years, Zika virus (ZIKV) has expanded its geographic range and in 2015–2016 caused a substantial epidemic linked to a surge in developmental and neurological complications in newborns. Mathematical models are powerful tools for assessing ZIKV spread and can reveal important information for preventing future outbreaks. We reviewed the literature and retrieved modelling studies that were developed to understand the spatial epidemiology of ZIKV spread and risk. We classified studies by type, scale, aim and applications and discussed their characteristics, strengths and limitations. We examined the main objectives of these models and evaluated the effectiveness of integrating epidemiological and phylogeographic data, along with socioenvironmental risk factors that are known to contribute to vector–human transmission. We also assessed the promising application of human mobility data as a real-time indicator of ZIKV spread. Lastly, we summarised model validation methods used in studies to ensure accuracy in models and modelled outcomes. Models are helpful for understanding ZIKV spread and their characteristics should be carefully considered when developing future modelling studies to improve arbovirus surveillance.

Zika virus envelope nanoparticle antibodies protect mice without risk of disease enhancement

Background

Zika virus (ZIKV), an arbovirus capable of causing neurological abnormalities, is a recognised human pathogen, for which a vaccine is required. As ZIKV antibodies can mediate antibody-dependent enhancement (ADE) of dengue virus (DENV) infection, a ZIKV vaccine must not only protect against ZIKV but must also not sensitise vaccinees to severe dengue.

Methods

The N-terminal 80% of ZIKV envelope protein (80E) was expressed in Pichia pastoris and its capacity to self-assemble into particulate structures evaluated using dynamic light scattering and electron microscopy. Antigenic integrity of the 80E protein was evaluated using ZIKV-specific monoclonal antibodies. Its immunogenicity and protective efficacy were assessed in BALB/c and C57BL/6 Stat2^−/− mice, respectively. Its capacity to enhance DENV and ZIKV infection was assessed in AG129 and C57BL/6 Stat2^−/− mice, respectively.

Findings

ZIKV-80E protein self-assembled into discrete nanoparticles (NPs), which preserved the antigenic integrity of neutralising epitopes on E domain III (EDIII) and elicited potent ZIKV-neutralising antibodies predominantly against this domain in BALB/c mice. These antibodies conferred statistically significant protection in vivo (p = 0.01, Mantel–Cox test), and did not exacerbate sub-lethal DENV-2 or ZIKV challenges in vivo.

Interpretation

Yeast-expressed ZIKV-80E, which forms highly immunogenic EDIII-displaying NPs, elicits ZIKV EDIII-specific antibodies capable of offering significant protection in vivo, without the potential risk of ADE upon subsequent DENV-2 or ZIKV infection. This offers a promising vaccine candidate for further development.

Funding

This study was supported partly by ICGEB, India, and by NIAID, USA.

Mapping the cryptic spread of the 2015-2016 global Zika virus epidemic

BACKGROUND

Zika virus (ZIKV) emerged as a global epidemic in 2015-2016 from Latin America with its true geographical extent remaining unclear due to widely presumed underreporting. The identification of locations with potential and unknown spread of ZIKV is a key yet understudied component for outbreak preparedness. Here, we aim to identify locations at a high risk of cryptic ZIKV spread during 2015-2016 to further the understanding of the global ZIKV epidemiology, which is critical for the mitigation of the risk of future epidemics.

METHODS

We developed an importation simulation model to estimate the weekly number of ZIKV infections imported in each susceptible spatial unit (i.e. location that did not report any autochthonous Zika cases during 2015-2016), integrating epidemiological, demographic, and travel data as model inputs. Thereafter, a global risk model was applied to estimate the weekly ZIKV transmissibility during 2015-2016 for each location. Finally, we assessed the risk of onward ZIKV spread following importation in each susceptible spatial unit to identify locations with a high potential for cryptic ZIKV spread during 2015-2016.

RESULTS

We have found 24 susceptible spatial units that were likely to have experienced cryptic ZIKV spread during 2015-2016, of which 10 continue to have a high risk estimate within a highly conservative scenario, namely, Luanda in Angola, Banten in Indonesia, Maharashtra in India, Lagos in Nigeria, Taiwan and Guangdong in China, Dakar in Senegal, Maputo in Mozambique, Kinshasa in Congo DRC, and Pool in Congo. Notably, among the 24 susceptible spatial units identified, some have reported their first ZIKV outbreaks since 2017, thus adding to the credibility of our results (derived using 2015-2016 data only).

CONCLUSION

Our study has provided valuable insights into the potentially high-risk locations for cryptic ZIKV circulation during the 2015-2016 pandemic and has also laid a foundation for future studies that attempt to further narrow this key knowledge gap. Our modelling framework can be adapted to identify areas with likely unknown spread of other emerging vector-borne diseases, which has important implications for public health readiness especially in resource-limited settings.

Risk mapping of scrub typhus infections in Qingdao city, China

BACKGROUND

The emergence and re-emergence of scrub typhus has been reported in the past decade in many global regions. In this study, we aim to identify potential scrub typhus infection risk zones with high spatial resolution in Qingdao city, in which scrub typhus is endemic, to guide local prevention and control strategies.

METHODOLOGY/PRINCIPAL FINDINGS

Scrub typhus cases in Qingdao city during 2006-2018 were retrieved from the Chinese National Infectious Diseases Reporting System. We divided Qingdao city into 1,101 gridded squares and classified them into two categories: areas with and without recorded scrub typhus cases. A boosted regression tree model was used to explore environmental and socioeconomic covariates associated with scrub typhus occurrence and predict the risk of scrub typhus infection across the whole area of Qingdao city. A total of 989 scrub typhus cases were reported in Qingdao from 2006-2018, with most cases located in rural and suburban areas. The predicted risk map generated by the boosted regression tree models indicated that the highest infection risk areas were mainly concentrated in the mid-east and northeast regions of Qingdao, with gross domestic product (20.9%±1.8% standard error) and annual cumulative precipitation (20.3%±1.1%) contributing the most to the variation in the models. By using a threshold environmental suitability value of 0.26, we identified 757 squares (68.7% of the total) with a favourable environment for scrub typhus infection; 66.2% (501/757) of the squares had not yet recorded cases. It is estimated that 6.32 million people (72.5% of the total population) reside in areas with a high risk of scrub typhus infection.

CONCLUSIONS/SIGNIFICANCE

Many locations in Qingdao city with no recorded scrub typhus cases were identified as being at risk for scrub typhus occurrence. In these at-risk areas, awareness and capacity for case diagnosis and treatment should be enhanced in the local medical service institutes.

Mapping Thermal Physiology of Vector-Borne Diseases in a Changing Climate: Shifts in Geographic and Demographic Risk of Suitability

PURPOSE OF REVIEW

To describe a collection of recent work published on thermal suitability for vector-borne diseases, in which mapping approaches illustrated the geographic shifts, and spatial approaches describe the demographic impact anticipated with a changing climate.

RECENT FINDINGS

While climate change predictions of warming indicate an expansion in VBD suitability risk in some parts of the globe, while in others, optimal temperatures for transmission may be exceeded, as seen for malaria in Western Africa, resulting in declining risk. The thermal suitability of specific vector-pathogen pairs can have large impacts on geographic range of risk, and changes in human demography itself will intersect with this risk to create different vulnerability profiles over the coming century. Using a physiological approach to describe the thermal suitability of transmission for vector-borne diseases allows us to illustrate the future risk as mapped information. This in turn can be coupled with demographic projections to anticipate changing risk, and even changing vulnerability within that population change.

Parental Stress in Primary Caregivers of Children with Evidence of Congenital Zika Virus Infection in Northeastern Brazil

BACKGROUND

Despite the well-known role of parents as caregivers, few studies have addressed their health outcomes related to the Zika virus epidemic.

METHODS

A cross-sectional study was carried out with 146 primary caregivers of children 15-26 months of age, with laboratory and/or clinical evidence of Zika infection between August and October 2017 in three Brazilian municipalities: João Pessoa and Campina Grande in the state of Paraíba and Fortaleza in the state of Ceará. Caregivers reported on their child's life and health, family circumstances and underwent screening for stress using the Parenting Stress Index-Short Form. Children were evaluated for developmental delays and clinical outcomes. Differences in the prevalence of risk factors between caregivers with high or clinically relevant stress and those with normal stress were evaluated.

RESULTS

Of the 146 participants, 13% (n = 19) were classified as having high or clinically relevant stress, all of them mothers. The two risk factors significantly and independently associated with high levels of stress, compared with individuals with normal stress levels, were "reporting difficulty in covering basic expenses" (adjusted OR 3.6 (95% CI 1.1-11.8; p = 0.034)) and "having a child with sleep problems" (adjusted OR 10.4 (95% CI 1.3-81.7; p = 0.026)).

CONCLUSIONS

Some factors seem to contribute significantly more than others to the level of stress experienced by caregivers of children with evidence of Zika virus congenital infection. Interventions and preventive strategies should also target caregivers, who in turn will be able to respond to the unique characteristics of their child.

Of Mice and Fungi: Coccidioides spp. Distribution Models

The continuous increase of Coccidioidomycosis cases requires reliable detection methods of the causal agent, Coccidioides spp., in its natural environment. This has proven challenging because of our limited knowledge on the distribution of this soil-dwelling fungus. Knowing the pathogen’s geographic distribution and its relationship with the environment is crucial to identify potential areas of risk and to prevent disease outbreaks. The maximum entropy (Maxent) algorithm, Geographic Information System (GIS) and bioclimatic variables were combined to obtain current and future potential distribution models (DMs) of Coccidioides and its putative rodent reservoirs for Arizona, California and Baja California. We revealed that Coccidioides DMs constructed with presence records from one state are not well suited to predict distribution in another state, supporting the existence of distinct phylogeographic populations of Coccidioides. A great correlation between Coccidioides DMs and United States counties with high Coccidioidomycosis incidence was found. Remarkably, under future scenarios of climate change and high concentration of greenhouse gases, the probability of habitat suitability for Coccidioides increased. Overlap analysis between the DMs of rodents and Coccidioides, identified Neotoma lepida as one of the predominant co-occurring species in all three states. Considering rodents DMs would allow to implement better surveillance programs to monitor disease spread.

Mapping the global potential transmission hotspots for severe fever with thrombocytopenia syndrome by machine learning methods

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with increasing spread. Currently SFTS transmission has expanded beyond Asian countries, however, with definitive global extents and risk patterns remained obscure. Here we established an exhaustive database that included globally reported locations of human SFTS cases and the competent vector, Haemaphysalis longicornis (H. longicornis), as well as the explanatory environmental variables, based on which, the potential geographic range of H. longicornis and risk areas for SFTS were mapped by applying two machine learning methods. Ten predictors were identified contributing to global distribution for H. longicornis with relative contribution ≥1%. Outside contemporary known distribution, we predict high receptivity to H. longicornis across two continents, including northeastern USA, New Zealand, parts of Australia, and several Pacific islands. Eight key drivers of SFTS cases occurrence were identified, including elevation, predicted probability of H. longicornis presence, two temperature-related factors, two precipitation-related factors, the richness of mammals and percentage coverage of water bodies. The globally model-predicted risk map of human SFTS occurrence was created and validated effective for discriminating the actual affected and unaffected areas (median predictive probability 0.74 vs. 0.04, P < 0.001) in three countries with reported cases outside China. The high-risk areas (probability ≥50%) were predicted mainly in east-central China, most parts of the Korean peninsula and southern Japan, and northern New Zealand. Our findings highlight areas where an intensive vigilance for potential SFTS spread or invasion events should be advocated, owing to their high receptibility to H. longicornis distribution.

Clinical Symptoms of Arboviruses in Mexico

Arboviruses such as Chikungunya (CHIKV), Dengue (DENV), and Zika virus (ZIKV) have emerged as a significant public health concern in Mexico. The existing literature lacks evidence regarding the dispersion of arboviruses, thereby limiting public health policy's ability to integrate the diagnosis, management, and prevention. This study seeks to reveal the clinical symptoms of CHIK, DENV, and ZIKV by age group, region, sex, and time across Mexico. The confirmed cases of CHIKV, DENV, and ZIKV were compiled from January 2012 to March 2020. Demographic characteristics analyzed significant clinical symptoms of confirmed cases. Multinomial logistic regression was used to assess the association between clinical symptoms and geographical regions. Females and individuals aged 15 and older had higher rates of reported significant symptoms across all three arboviruses. DENV showed a temporal variation of symptoms by regions 3 and 5, whereas ZIKV presented temporal variables in regions 2 and 4. This study revealed unique and overlapping symptoms between CHIKV, DENV, and ZIKV. However, the differentiation of CHIKV, DENV, and ZIKV is difficult, and diagnostic facilities are not available in rural areas. There is a need for adequately trained healthcare staff alongside well-equipped lab facilities, including hematological tests and imaging facilities.

Informing Rift Valley Fever preparedness by mapping seasonally varying environmental suitability

BACKGROUND

Rift Valley Fever (RVF) poses a threat to human and animal health throughout much of Africa and the Middle East and has been recognized as a global health security priority and a key preparedness target.

METHODS

We combined RVF occurrence data from a systematic literature review with animal notification data from an online database. Using boosted regression trees, we made monthly environmental suitability predictions from January 1995 to December 2016 at a 5 × 5-km resolution throughout regions of Africa, Europe, and the Middle East. We calculated the average number of months per year suitable for transmission, the mean suitability for each calendar month, and the "spillover potential," a measure incorporating suitability with human and livestock populations.

RESULTS

Several countries where cases have not yet been reported are suitable for RVF. Areas across the region of interest are suitable for transmission at different times of the year, and some areas are suitable for multiple seasons each year. Spillover potential results show areas within countries where high populations of humans and livestock are at risk for much of the year.

CONCLUSIONS

The widespread environmental suitability of RVF highlights the need for increased preparedness, even in countries that have not previously experienced cases. These maps can aid in prioritizing long-term RVF preparedness activities and determining optimal times for recurring preparedness activities. Given an outbreak, our results can highlight areas often at risk for subsequent transmission that month, enabling decision-makers to target responses effectively.

Brazil's Missing Infants: Zika Risk Changes Reproductive Behavior

Zika virus epidemics have potential large-scale population effects. Controlled studies of mice and nonhuman primates indicate that Zika affects fecundity, raising concerns about miscarriage in human populations. In regions of Brazil, Zika risk peaked months before residents learned about the epidemic and its relation to congenital anomalies. This spatiotemporal variation supports analysis of both biological effects of Zika infection on fertility and the effects of learning about Zika risk on reproductive behavior. Causal inference techniques used with vital statistics indicate that the epidemic caused reductions in birth cohort size of approximately one-quarter 18 months after Zika infection risk peaked but 10 months after public health messages advocated childbearing delay. The evidence is consistent with small but not statistically detectable biological reductions in fecundity, as well as large strategic changes in reproductive behavior to temporally align childbearing with reduced risk to infant health. The behavioral effects are larger for more-educated and older women, which may reflect facilitated access to information and to family planning services within high-risk, mosquito-infested urban locations as well as perceptions about the opportunity costs of risks to pregnancy and infant survival.

Leveraging multiple data types to estimate the size of the Zika epidemic in the Americas

Several hundred thousand Zika cases have been reported across the Americas since 2015. Incidence of infection was likely much higher, however, due to a high frequency of asymptomatic infection and other challenges that surveillance systems faced. Using a hierarchical Bayesian model with empirically-informed priors, we leveraged multiple types of Zika case data from 15 countries to estimate subnational reporting probabilities and infection attack rates (IARs). Zika IAR estimates ranged from 0.084 (95% CrI: 0.067–0.096) in Peru to 0.361 (95% CrI: 0.214–0.514) in Ecuador, with significant subnational variability in every country. Totaling infection estimates across these and 33 other countries and territories, our results suggest that 132.3 million (95% CrI: 111.3-170.2 million) people in the Americas had been infected by the end of 2018. These estimates represent the most extensive attempt to determine the size of the Zika epidemic in the Americas, offering a baseline for assessing the risk of future Zika epidemics in this region.

During the recent Zika epidemic in the Americas millions of people were likely infected, but the true size of the epidemic is unknown because of gaps in the surveillance system. The infection attack rate (IAR)—defined as the proportion of the population that was infected over the course of the epidemic—has important implications for the longer-term epidemiology of Zika in the region, such as the timing, location, and likelihood of future outbreaks. To estimate the IAR and the total number of people infected, we leveraged multiple types of Zika case data from 15 countries and territories where subnational data were publicly available. Datasets included confirmed and suspected Zika cases in pregnant women and in the total population, Zika-associated Guillan-Barré syndrome cases, and cases of congenital Zika syndrome. We used a hierarchical Bayesian model with empirically-informed priors that leveraged the different case report types to simultaneously estimate national and subnational reporting probabilities, the fraction of symptomatic infections, and subnational IARs. In these 15 countries and territories, estimates of Zika IAR ranged from 0.084 (95% CrI: 0.067–0.096) in Peru to 0.361 (95% CrI: 0.214–0.514) in Ecuador. Totaling these infection estimates across these and 33 other countries and territories in the region, our results suggest that 132.3 million (95% CrI: 111.3-170.2 million) people in the Americas were infected with ZIKV by the end of 2018.

Protective and enhancing interactions among dengue viruses 1-4 and Zika virus

Dengue viruses 1-4 (DENV 1-4) and Zika virus (ZIKV) are closely related flaviviruses transmitted by Aedes mosquitoes that co-circulate in Asia, the Americas, Africa, and Oceania. Here, we review recent and historical literature on in vitro experiments, animal models, and clinical and epidemiological studies to describe how the sequence of DENV 1-4 and ZIKV infections modulates subsequent dengue and Zika disease outcome. Overall, we find these interactions are asymmetric. Immunity from a prior DENV infection or a prior ZIKV infection can enhance future severe dengue disease for some DENV serotypes while protecting against other serotypes. Further, prior DENV immunity has not been shown to enhance future uncomplicated or severe Zika and instead appears to be protective. Interestingly, secondary ZIKV infection induces type-specific ZIKV immunity but only generates weakly cross-neutralizing anti-DENV/ZIKV immunity, consistent with risk of future dengue disease. In contrast, secondary DENV infection induces strongly cross-neutralizing antibodies that protect against subsequent severe dengue disease. These immunologic interactions may be explained by differences in virion structure between DENV 1-4 and ZIKV, which modulate thermostability, susceptibility to neutralization, and cell infectivity. Overall, these observations are important for the understanding and prediction of epidemics and the development and evaluation of dengue and Zika vaccines.

Spatial risk analysis for the introduction and circulation of six arboviruses in the Netherlands

Background

Arboviruses are a growing public health concern in Europe, with both endemic and exotic arboviruses expected to spread further into novel areas in the next decades. Predicting where future outbreaks will occur is a major challenge, particularly for regions where these arboviruses are not endemic. Spatial modelling of ecological risk factors for arbovirus circulation can help identify areas of potential emergence. Moreover, combining hazard maps of different arboviruses may facilitate a cost-efficient, targeted multiplex-surveillance strategy in areas where virus transmission is most likely. Here, we developed predictive hazard maps for the introduction and/or establishment of six arboviruses that were previously prioritized for the Netherlands: West Nile virus, Japanese encephalitis virus, Rift Valley fever virus, tick-borne encephalitis virus, louping-ill virus and Crimean-Congo haemorrhagic fever virus.

Methods

Our spatial model included ecological risk factors that were identified as relevant for these arboviruses by an earlier systematic review, including abiotic conditions, vector abundance, and host availability. We used geographic information system (GIS)-based tools and geostatistical analyses to model spatially continuous datasets on these risk factors to identify regions in the Netherlands with suitable ecological conditions for arbovirus introduction and establishment.

Results

The resulting hazard maps show that there is spatial clustering of areas with either a relatively low or relatively high environmental suitability for arbovirus circulation. Moreover, there was some overlap in high-hazard areas for virus introduction and/or establishment, particularly in the southern part of the country.

Conclusions

The similarities in environmental suitability for some of the arboviruses provide opportunities for targeted sampling of vectors and/or sentinel hosts in these potential hotspots of emergence, thereby increasing the efficient use of limited resources for surveillance.

Spatiotemporal Patterns and Risk Factors for Scrub Typhus From 2007 to 2017 in Southern China

BACKGROUND

Substantial outbreaks of scrub typhus, coupled with the discovery of this vector-borne disease in new areas, suggest that the disease remains remarkably neglected. The objectives of this study were to map the contemporary and potential transmission risk zones of the disease and to provide novel insights into the health burden imposed by scrub typhus in southern China.

METHODS

Based on the assembled data sets of annual scrub typhus cases and maps of environmental and socioeconomic correlates, a boosted regression tree modeling procedure was used to identify the environmental niche of scrub typhus and to predict the potential infection zones of the disease. Additionally, we estimated the population living in the potential scrub typhus infection areas in southern China.

RESULTS

Spatiotemporal patterns of the annual scrub typhus cases in southern China between 2007 and 2017 reveal a tremendous, wide spread of scrub typhus. Temperature, relative humidity, elevation, and the normalized difference vegetation index are the main factors that influence the spread of scrub typhus. In southern China, the predicted highest transmission risk areas of scrub typhus are mainly concentrated in several regions, such as Yunnan, Guangxi, Guangdong, Hainan, and Fujian. We estimated that 162 684 million people inhabit the potential infection risk zones in southern China.

CONCLUSIONS

Our results provide a better understanding of the environmental and socioeconomic factors driving scrub typhus spread, and estimate the potential infection risk zones beyond the disease's current, limited geographical extent, which enhances our capacity to target biosurveillance and help public health authorities develop disease control strategies.

The Midgut Microbiota of Colombian Aedes aegypti Populations with Different Levels of Resistance to the Insecticide Lambda-cyhalothrin

Insecticide resistance in Aedes aegypti populations is a problem that hinders vector control and dengue prevention programs. In this study, we determined the susceptibility of Ae. aegypti populations from six Colombian regions to the pyrethroid lambda-cyhalothrin and evaluated the presence of the V1016I mutation in the sodium channel gene, which has been broadly involved in the resistance to this insecticide. The diversity of the gut microbiota of these mosquito populations was also analyzed. Only mosquitoes from Bello were susceptible to lambda-cyhalothrin and presented a lower allelic frequency of the V1016I mutation. Remarkably, there was not an important change in allelic frequencies among populations with different resistance ratios, indicating that other factors or mechanisms contributed to the resistant phenotype. Treatment of mosquitoes with antibiotics led us to hypothesize that the intestinal microbiota could contribute to the resistance to lambda-cyhalothrin. Beta diversity analysis showed significant differences in the species of bacteria present between susceptible and resistant populations. We identified 14 OTUs of bacteria that were unique in resistant mosquitoes. We propose that kdr mutations are important in the development of resistance to lambda-cyhalothrin at low insecticide concentrations but insect symbionts could play an essential role in the metabolization of pyrethroid insecticides at higher concentrations, contributing to the resistant phenotype in Ae. aegypti.

Aedes-borne disease outbreaks in West Africa: A call for enhanced surveillance

Arboviruses transmitted by Aedes mosquitoes are a growing global concern; however, there remain large gaps in surveillance of both arboviruses and their vectors in West Africa. We reviewed over 50 years of data including outbreak reports, peer-reviewed literature, and prior data compilations describing Zika, dengue, and chikungunya, and their vectors in West Africa. Large outbreaks of dengue, Zika, and chikungunya have recently occurred in the region with over 27,000 cases of Aedes-borne disease documented since 2007. Recent arboviral outbreaks have become more concentrated in urban areas, and Aedes albopictus, recently documented in the region, has emerged as an important vector in several areas. Seroprevalence surveys suggest reported cases are a gross underestimate of the underlying arboviral disease burden. These findings indicate a shifting epidemiology of arboviral disease in West Africa and highlight a need for increased research and implementation of vector and disease control. Rapid urbanization and climate change may further alter disease patterns, underscoring the need for improved diagnostic capacity, and vector and disease surveillance to address this evolving health challenge.

MODELING ZIKA TRANSMISSION DYNAMICS: PREVENTION AND CONTROL

The Zika virus (ZIKV) epidemic is depicted to have high spatial diversity and slow growth, attributable to the dynamics of the mosquito vector and mobility of the human populations. In an effort to understand the transmission dynamics of Zika virus, we formulate a new compartmental epidemic model with a system of seven differential equations and 11 parameters incorporating the decaying transmission rate and study the impact of protection measure on basic public health. We do not fit the model to the observed pattern of spread, rather we use parameter values estimated in the past and examine the extent to which the designed model prediction agrees with the pattern of spread seen in Brazil, via reaction–diffusion modeling. Our work includes estimation of key epidemiological parameters such as basic reproduction number ([Formula: see text], and gives a rough estimate of how many individuals can be typically infected during an outbreak if it occurs in India. We used partial rank correlation coefficient method for global sensitivity analysis to identify the most influential model parameters. Using optimal control theory and Pontryagin’s maximum principle, a control model has been proposed and conditions for the optimal control are determined for the deterministic model of Zika virus. The control functions for the strategies (i) vector-to-human contact reduction and (ii) vector elimination are introduced into the system. Numerical simulations are also performed. This work aimed at understanding the potential extent and timing of the ZIKV epidemic can be used as a template for the analysis of future mosquito-borne epidemics.

AeDES: a next-generation monitoring and forecasting system for environmental suitability of Aedes-borne disease transmission

Aedes-borne diseases, such as dengue and chikungunya, are responsible for more than 50 million infections worldwide every year, with an overall increase of 30-fold in the last 50 years, mainly due to city population growth, more frequent travels and ecological changes. In the United States of America, the vast majority of Aedes-borne infections are imported from endemic regions by travelers, who can become new sources of mosquito infection upon their return home if the exposed population is susceptible to the disease, and if suitable environmental conditions for the mosquitoes and the virus are present. Since the susceptibility of the human population can be determined via periodic monitoring campaigns, the environmental suitability for the presence of mosquitoes and viruses becomes one of the most important pieces of information for decision makers in the health sector. We present a next-generation monitoring and forecasting system for [Formula: see text]-borne diseases' environmental suitability (AeDES) of transmission in the conterminous United States and transboundary regions, using calibrated ento-epidemiological models, climate models and temperature observations. After analyzing the seasonal predictive skill of AeDES, we briefly consider the recent Zika epidemic, and the compound effects of the current Central American dengue outbreak happening during the SARS-CoV-2 pandemic, to illustrate how a combination of tailored deterministic and probabilistic forecasts can inform key prevention and control strategies .

Efficacy and Spatial Extent of Yard-Scale Control of Aedes (Stegomyia) albopictus (Diptera: Culicidae) Using Barrier Sprays and Larval Habitat Management

The Asian tiger mosquito, Aedes (Stegomyia) albopictus (Skuse), is a peridomestic, container-ovipositing mosquito commonly found throughout the southeastern United States. In the United States, Ae. albopictus is typically considered a nuisance pest; however, it is capable of transmitting multiple pathogens. Ae. albopictus is an important pest species and the target of numerous mosquito control efforts in the United States. Here, we evaluate the effectiveness and spatial extent of Ae. albopictus population reduction using a bifenthrin (AI Bifen IT, 7.9%) barrier spray and larval habitat management (LHM) in a temperate, suburban setting. Sixteen pairs of adjoining neighbors were randomly assigned to treatment groups with one neighbor receiving a treatment and the other monitored for evidence of a spillover effect of the treatments. Ae. albopictus populations in both yards were monitored for 33 d, with treatments occurring on the eighth day. Barrier sprays, both alone and combined with LHM, resulted in a significant reduction in Ae. albopictus abundance posttreatment. While LHM alone did not result in a significant reduction over the entire posttreatment period, Ae. albopictus populations were observed to be in decline during this period. No treatments were observed to have any reduction in efficacy 25 d posttreatment, with treatments involving LHM having a significantly increased efficacy. Yards neighboring treated yards were also observed to have reduced population sizes posttreatment, but these differences were rarely significant. These results provide insights into the population dynamics of Ae. albopictus following two common treatments and will be useful for integrated pest management plans.

Population structure across scales facilitates coexistence and spatial heterogeneity of antibiotic-resistant infections

Antibiotic-resistant infections are a growing threat to human health, but basic features of the eco-evolutionary dynamics remain unexplained. Most prominently, there is no clear mechanism for the long-term coexistence of both drug-sensitive and resistant strains at intermediate levels, a ubiquitous pattern seen in surveillance data. Here we show that accounting for structured or spatially-heterogeneous host populations and variability in antibiotic consumption can lead to persistent coexistence over a wide range of treatment coverages, drug efficacies, costs of resistance, and mixing patterns. Moreover, this mechanism can explain other puzzling spatiotemporal features of drug-resistance epidemiology that have received less attention, such as large differences in the prevalence of resistance between geographical regions with similar antibiotic consumption or that neighbor one another. We find that the same amount of antibiotic use can lead to very different levels of resistance depending on how treatment is distributed in a transmission network. We also identify parameter regimes in which population structure alone cannot support coexistence, suggesting the need for other mechanisms to explain the epidemiology of antibiotic resistance. Our analysis identifies key features of host population structure that can be used to assess resistance risk and highlights the need to include spatial or demographic heterogeneity in models to guide resistance management.

Knowledge, attitudes and bite prevention practices and estimation of productivity of vector breeding sites using a Habitat Suitability Score (HSS) among households with confirmed dengue in the 2014 outbreak in Dar es Salaam, Tanzania

BACKGROUND

The frequency and magnitude of dengue epidemics has increased dramatically throughout the tropics in the past 40 years due to unplanned urbanization, globalization and lack of effective mosquito control. The commercial capital of Tanzania, Dar es Salaam, is now experiencing regular dengue outbreaks. Three dengue serotypes have been detected in Dar es Salaam (DNV 1, 2 and 3). Without adequate vector monitoring and control, further outbreaks will certainly occur.

METHODS/FINDINGS

A case series study followed 97 individuals with confirmed dengue fever (NS1 and/or IgM on rapid diagnostic test and/or PCR positive) to their households in Kinondoni, Dar es Salaam during the 2014 outbreak from a random sample of 202 confirmed cases at Mwananyamala Hospital. Kinondoni wards of Manzese, Mwananyamala, Tandale and Mabibo had the highest number of confirmed cases: 18, 13, 13 and 9 respectively. Individuals were interviewed by questionnaire on dengue prevention practices and houses were inspected for mosquito breeding sites to validate a Habitat Suitability Score (HSS). This is a tool devised to predict the productivity of any potential breeding habitats (PBHs) before the rains begin. There were 12 /312 positive Aedes breeding habitats. Drums/barrels, flowerpots and tyres were the most common breeding habitats. The HSS correctly identified 9/12 of Aedes breeding habitats. Larviciding is already conducted in urban Tanzania for malaria control and the HSS may be a useful means to train individuals on productive Aedes aegypti breeding sites should this program be extended to include dengue control. The population remains poorly informed about dengue transmission and prevention: 22% of respondents said dengue is spread from one person to another and 60% first heard about dengue when already sick. Less than 20% of respondents used personal protection and >80% thought bednets protected against dengue. Mobile phones were owned by almost all individuals followed up and have the potential of being the prime medium for dissemination of information on dengue prevention.

Real-time Epidemic Forecasting: Challenges and Opportunities

Infectious disease outbreaks play an important role in global morbidity and mortality. Real-time epidemic forecasting provides an opportunity to predict geographic disease spread as well as case counts to better inform public health interventions when outbreaks occur. Challenges and recent advances in predictive modeling are discussed here. We identified data needs in the areas of epidemic surveillance, mobility, host and environmental susceptibility, pathogen transmissibility, population density, and healthcare capacity. Constraints in standardized case definitions and timely data sharing can limit the precision of predictive models. Resource-limited settings present particular challenges for accurate epidemic forecasting due to the lack of granular data available. Incorporating novel data streams into modeling efforts is an important consideration for the future as technology penetration continues to improve on a global level. Recent advances in machine-learning, increased collaboration between modelers, the use of stochastic semi-mechanistic models, real-time digital disease surveillance data, and open data sharing provide opportunities for refining forecasts for future epidemics. Epidemic forecasting using predictive modeling is an important tool for outbreak preparedness and response efforts. Despite the presence of some data gaps at present, opportunities and advancements in innovative data streams provide additional support for modeling future epidemics.

Emergence of Zika virus infection in China

Currently, Zika virus (ZIKV) is spreading across the world and no ZIKV infection cases have ever been reported in China. Here, we aimed to determine whether ZIKV infection exists in China. Blood samples of 273 healthy individuals were collected from Nanning City, Guangxi Province, China in March 2019. We found that 9.5% (26/273) and 1.8% (5/273) of healthy persons were positive to ZIKV total antibody (IgG and/or IgM) IgM antibody, respectively. All ZIKV positive plasma samples were negative to Dengue virus and West Nile virus. Among the ZIKV antibody positive plasma samples, 65.4% (17/26) exhibited neutralizing activity to ZIKV. Followed up studies showed that none had clinical symptoms of ZIKV infection and oversea experience. Together, our study indicates that endemic ZIKV infections emerge in China, which not only suggested that ZIKV posed a potential threat to public health in China, but also expand the ZIKV epidemic areas in East and Southeast Asia.

Current and Projected Distributions of Aedes aegypti and Ae. albopictus in Canada and the U.S

BACKGROUND

Aedes aegypti and Ae. albopictus are mosquito vectors of more than 22 arboviruses that infect humans.

OBJECTIVES

Our objective was to develop regional ecological niche models for Ae. aegypti and Ae. albopictus in the conterminous United States and Canada with current observed and simulated climate and land-use data using boosted regression trees (BRTs).

METHODS

We used BRTs to assess climatic suitability for Ae. albopictus and Ae. aegypti mosquitoes in Canada and the United States under current and future projected climates.

RESULTS

Models for both species were mostly influenced by minimum daily temperature and demonstrated high accuracy for predicting their geographic ranges under the current climate. The northward range expansion of suitable niches for both species was projected under future climate models. Much of the United States and parts of southern Canada are projected to be suitable for both species by 2100, with Ae. albopictus projected to expand its range north earlier this century and further north than Ae. aegypti.

DISCUSSION

Our projections suggest that the suitable ecological niche for Aedes will expand with climate change in Canada and the United States, thus increasing the risk of Aedes-transmitted arboviruses. Increased surveillance for these vectors and the pathogens they carry would be prudent. https://doi.org/10.1289/EHP5899.

Comprehensive Profiling of Zika Virus Risk with Natural and Artificial Mitigating Strategies, United States

Zika virus is transitioning to become a long-term public health challenge, and countries should remain informed of the risk for emergence. We developed a stochastic epidemiologic model to profile risk for Zika virus emergence, including trimester-specific fetal risk across time, in all 3,208 counties in the United States, including Puerto Rico. Validation against known transmission in North America demonstrated accuracy to predict epidemic dynamics and absolute case counts across scales (R² = 0.98). We found that, although sporadic single transmission events could occur in most US counties, outbreaks will likely be restricted to the Gulf Coast region and to late spring through autumn. Seasonal fluctuations in birth rates will confer natural population-level protection against early-trimester infections. Overall, outbreak control will be more effective and efficient than prevention, and vaccination will be most effective at >70% coverage. Our county-level risk profiles should serve as a critical resource for resource allocation.

New estimates of the Zika virus epidemic attack rate in Northeastern Brazil from 2015 to 2016: A modelling analysis based on Guillain-Barré Syndrome (GBS) surveillance data

BACKGROUND

Between January 2015 and August 2016, two epidemic waves of Zika virus (ZIKV) disease swept the Northeastern (NE) region of Brazil. As a result, two waves of Guillain-Barré Syndrome (GBS) were observed concurrently. The mandatory reporting of ZIKV disease began region-wide in February 2016, and it is believed that ZIKV cases were significantly under-reported before that. The changing reporting rate has made it difficult to estimate the ZIKV infection attack rate, and studies in the literature vary widely from 17% to > 50%. The same applies to other key epidemiological parameters. In contrast, the diagnosis and reporting of GBS cases were reasonably reliable given the severity and easy recognition of the disease symptoms. In this paper, we aim to estimate the real number of ZIKV cases (i.e., the infection attack rate) and their dynamics in time, by scaling up from GBS surveillance data in NE Brazil.

METHODOLOGY

A mathematical compartmental model is constructed that makes it possible to infer the true epidemic dynamics of ZIKV cases based on surveillance data of excess GBS cases. The model includes the possibility that asymptomatic ZIKV cases are infectious. The model is fitted to the GBS surveillance data and the key epidemiological parameters are inferred by using a plug-and-play likelihood-based estimation. We make use of regional weather data to determine possible climate-driven impacts on the reproductive number [Formula: see text], and to infer the true ZIKV epidemic dynamics.

FINDINGS AND CONCLUSIONS

The GBS surveillance data can be used to study ZIKV epidemics and may be appropriate when ZIKV reporting rates are not well understood. The overall infection attack rate (IAR) of ZIKV is estimated to be 24.1% (95% confidence interval: 17.1%-29.3%) of the population. By examining various asymptomatic scenarios, the IAR is likely to be lower than 33% over the two ZIKV waves. The risk rate from symptomatic ZIKV infection to develop GBS was estimated as ρ = 0.0061% (95% CI: 0.0050%-0.0086%) which is significantly less than current estimates. We found a positive association between local temperature and the basic reproduction number, [Formula: see text]. Our analysis revealed that asymptomatic infections affect the estimation of ZIKV epidemics and need to also be carefully considered in related modelling studies. According to the estimated effective reproduction number and population wide susceptibility, we comment that a ZIKV outbreak would be unlikely in NE Brazil in the near future.

Availability, access, analysis and dissemination of small-area data

In this era of 'big data', there is growing recognition of the value of environmental, health, social and demographic data for research. Open government data initiatives are growing in number and in terms of content. Remote sensing data are finding widespread use in environmental research, including in low- and middle-income settings. While our ability to study environment and health associations across countries and continents grows, data protection rules and greater patient control over the use of their data present new challenges to using health data in research. Innovative tools that circumvent the need for the physical sharing of data by supporting non-disclosive sharing of information, or that permit spatial analysis without researchers needing access to underlying patient data can be used to support analyses while protecting data confidentiality. User-friendly visualizations, allowing small-area data to be seen and understood by non-expert audiences, are revolutionizing public and researcher interactions with data. The UK Small Area Health Statistics Unit's Environment and Health Atlas for England and Wales, and the US National Environmental Public Health Tracking Network offer good examples. Open data facilitates user-generated outputs, and 'mash-ups', and user-generated inputs from social media, mobile devices and wearable tech are new data streams that will find utility in future studies, and bring novel dimensions with respect to ethical use of small-area data.

RNA-Dependent Structures of the RNA-Binding Loop in the Flavivirus NS3 Helicase

The flavivirus NS3 protein is a helicase that has pivotal functions during the viral genome replication process, where it unwinds double-stranded RNA and translocates along the nucleic acid polymer in a nucleoside triphosphate hydrolysis-dependent mechanism. Crystallographic and computational studies of the flavivirus NS3 helicase have identified the RNA-binding loop as an interesting structural element that may function as a component of the RNA-enhanced NTPase activity observed for this family of helicases. Microsecond-long unbiased molecular dynamics and extensive replica exchange umbrella sampling simulations of the Zika NS3 helicase have been performed to investigate the RNA dependence of this loop's structural conformations. Specifically, the effect of the bound single-stranded RNA (ssRNA) oligomer on the putative "open" and "closed" conformations of this loop is studied. In the Apo substrate state, the two loop conformations are nearly isoergonic (ΔAO→C = -0.22 kcal mol-1), explaining the structural ambiguity observed in Apo NS3h crystal structures. The bound ssRNA is seen to stabilize the "open" conformation (ΔAO→C = 1.97 kcal mol-1) through direct protein-RNA interactions at the top of the loop. Interestingly, a small ssRNA oligomer bound over 13 Å away from the loop is seen to affect the free energy surface to favor the "open" structure, while minimizing barriers between the two states. Both the mechanism of the "open" to "closed" transition and important residues of the RNA-binding loop structures are characterized. From these results, point mutations that are hypothesized to stabilize the "closed" RNA-binding loop and negatively impact RNA-binding and the RNA-enhanced NTPase activity are posited.

Strong CD4 T Cell Responses to Zika Virus Antigens in a Cohort of Dengue Virus Immune Mothers of Congenital Zika Virus Syndrome Infants

Background: There is an urgent need to understand the complex relationship between cross-reactive anti-viral immunity, disease susceptibility, and severity in the face of differential exposure to related, circulating Flaviviruses. Co-exposure to Dengue virus and Zika virus in Brazil is a case in point. A devastating aspect of the 2015-2016 South American Zika outbreak was the dramatic increase in numbers of infants born with microcephaly to mothers exposed to Zika virus during pregnancy. It has been proposed that this is more likely to ensue from Zika infection in women lacking cross-protective Dengue immunity. In this case series we measure the prevalence of Dengue immunity in a cohort of mothers exposed to Zika virus during pregnancy in the 2015-2016 Zika outbreak that gave birth to an infant affected by microcephaly and explore their adaptive immunity to Zika virus. Results: Fifty women from Sergipe, Brazil who gave birth to infants with microcephaly following Zika virus exposure during the 2015-16 outbreak were tested for serological evidence of Dengue exposure and IFNγ ELISpot spot forming cell (SFC) response to Zika virus. The majority (46/50) demonstrated Dengue immunity. IFNγ ELISpot responses to Zika virus antigens showed the following hierarchy: Env>NS1>NS3>C protein. Twenty T cell epitopes from Zika virus Env were identified. Responses to Zika virus antigens Env and NS1 were polyfunctional with cells making IFNγ, TNFα, IL-4, IL-13, and IL-10. In contrast, responses to NS5 only produced the immune regulatory TGFβ1 cytokine. There were SFC responses against Zika virus Env (1-20) and variant peptide sequences from West Nile virus, Dengue virus 1-4 and Yellow Fever virus. Conclusion: Almost all the women in our study showed serological evidence of Dengue immunity, suggesting that microcephaly can occur in DENV immune mothers. T cell immunity to Zika virus showed a multifunctional response to the antigens Env and NS1 and immune regulatory responses to NS5 and C protein. Our data support an argument that different viral products may skew the antiviral response to a more pro or anti-inflammatory outcome, with an associated impact on immunopathogenesis.

Spatial Associations Between Land Use and Infectious Disease: Zika Virus in Colombia

Land use boundaries represent human-physical interfaces where risk of vector-borne disease transmission is elevated. Land development practices, coupled with rural and urban land fragmentation, increases the likelihood that immunologically naïve humans will encounter infectious vectors at land use interfaces. This research consolidated land use classes from the GLC-SHARE dataset; calculated landscape metrics in linear (edge) density, proportion abundance, and patch density; and derived the incidence rate ratios of the Zika virus occurrence in Colombia, South America during 2016. Negative binomial regression was used to evaluate vector-borne disease occurrence counts in relation to Population Density, Average Elevation, Per Capita Gross Domestic Product, and each of three landscape metrics. Each kilometer of border length per square kilometer of area increase in the linear density of the Cropland and Grassland classes is associated with an increase in Zika virus risk. These spatial associations inform a risk reduction approach to rural and urban morphology and land development that emphasizes simple and compact land use geometry that decreases habitat availability for mosquito vectors of Zika virus.

Mapping Worldwide Environmental Suitability for Artemisia annua L

Artemisinin, which is isolated from the naturally occurring plant Artemisia annua L. (A. annua; Qinghao in traditional Chinese medicine), is considered to be the active ingredient in the most effective treatment for malaria. Current malaria eradication plans rely on an affordable and robust supply of artemisinin, resulting in the demand to expand the area of A. annua under cultivation. However, there is no reliable assessment of the potential land resources suitable for planting A. annua at the global scale. By explicitly incorporating the assembled contemporary occurrence records of A. annua with various spatial predictor variables, a species distribution modelling procedure was adopted to produce the first global environmental suitability map for A. annua with high geographic detail (5 × 5 km2). The estimated map reveals that the total amount of potential land resources suitable for planting A. annua is approximately 1496.56 million hectares, mainly distributed in Asia (516.50 million hectares), Europe (378.82 million hectares), North America (354.56 million hectares) and South America (172.01 million hectares). The relationships between the relevant variables and A. annua were explored, and these illustrated that the most noteworthy predictor variables were meteorological factors, followed by solar radiation factors, soil factors and topographical factors. The map provides a rigorous environmental niche baseline to support the reasonable expansion of the A. annua cultivation area.

Quantifying the risk of Zika virus spread in Asia during the 2015-16 epidemic in Latin America and the Caribbean: A modeling study

Background

No large-scale Zika epidemic has been observed to date in Southeast Asia following the 2015-16 Latin American and the Caribbean epidemic. One hypothesis is Southeast Asian populations’ partial immunity to Zika.

Method

We estimated the two conditions for a Zika outbreak emergence in Southeast Asia: (i) the risk of Zika introduction from Latin America and the Caribbean and, (ii) the risk of autochthonous transmission under varying assumptions on population immunity. We also validated the model used to estimate the risk of introduction by comparing the estimated number of Zika seeds introduced into the United States with case counts reported by the Centers for Disease Control and Prevention (CDC).

Results

There was good agreement between our estimates and case counts reported by the CDC. We thus applied the model to Southeast Asia and estimated that, on average, 1–10 seeds were introduced into Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam. We also found increasing population immunity levels from 0 to 90% reduced probability of autochthonous transmission by 40% and increasing individual variation in transmission further reduced the outbreak probability.

Conclusions

Population immunity, combined with heterogeneity in transmission, can explain why no large-scale outbreak was observed in Southeast Asia during the 2015-16 epidemic.