Transmission potential of Zika virus infection in the South Pacific

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.

A nonstandard finite difference scheme for a time-fractional model of Zika virus transmission

In this work, we investigate the transmission dynamics of the Zika virus, considering both a compartmental model involving humans and mosquitoes and an extended model that introduces a non-human primate (monkey) as a second reservoir host. The novelty of our approach lies in the later generalization of the model using a fractional time derivative. The significance of this study is underscored by its contribution to understanding the complex dynamics of Zika virus transmission. Unlike previous studies, we incorporate a non-human primate reservoir host into the model, providing a more comprehensive representation of the disease spread. Our results reveal the importance of utilizing a nonstandard finite difference (NSFD) scheme to simulate the disease's dynamics accurately. This NSFD scheme ensures the positivity of the solution and captures the correct asymptotic behavior, addressing a crucial limitation of standard solvers like the Runge-Kutta Fehlberg method (ode45). The numerical simulations vividly demonstrate the advantages of our approach, particularly in terms of positivity preservation, offering a more reliable depiction of Zika virus transmission dynamics. From these findings, we draw the conclusion that considering a non-human primate reservoir host and employing an NSFD scheme significantly enhances the accuracy and reliability of modeling Zika virus transmission. Researchers and policymakers can use these insights to develop more effective strategies for disease control and prevention.

Diel activity patterns of vector mosquito species in the urban environment: Implications for vector control strategies

Mathematical models have been widely used to study the population dynamics of mosquitoes as well as to test and validate the effectiveness of arbovirus outbreak responses and mosquito control strategies. The objective of this study is to assess the diel activity of mosquitoes in Miami-Dade, Florida, and Brownsville, Texas, the most affected areas during the Zika outbreak in 2016-2017, and to evaluate the effectiveness of simulated adulticide treatments on local mosquito populations. To assess variations in the diel activity patterns, mosquitoes were collected hourly for 96 hours once a month from May through November 2019 in Miami-Dade County, Florida, and Brownsville, Texas. We then performed a PERMANOVA followed by a SIMPER analysis to assess whether the abundance and species richness significantly varies at different hours of the day. Finally, we used a mathematical model to simulate the population dynamics of 5 mosquito vector species and evaluate the effectiveness of the simulated adulticide applications. A total of 14,502 mosquitoes comprising 17 species were collected in Brownsville and 10,948 mosquitoes comprising 19 species were collected in Miami-Dade County. Aedes aegypti was the most common mosquito species collected every hour in both cities and peaking in abundance in the morning and the evening. Our modeling results indicate that the effectiveness of adulticide applications varied greatly depending on the hour of the treatment. In both study locations, 9 PM was the best time for adulticide applications targeting all mosquito vector species; mornings/afternoons (9 AM- 5 PM) yielded low effectiveness, especially for Culex species, while at night (12 AM- 6 AM) the effectiveness was particularly low for Aedes species. Our results indicate that the timing of adulticide spraying interventions should be carefully considered by local authorities based on the ecology of the target mosquito species in the focus area.

Closing the gap to effective gene drive in Aedes aegypti by exploiting germline regulatory elements

CRISPR/Cas9-based homing gene drives have emerged as a potential new approach to mosquito control. While attempts have been made to develop such systems in Aedes aegypti, none have been able to match the high drive efficiency observed in Anopheles species. Here we generate Ae. aegypti transgenic lines expressing Cas9 using germline-specific regulatory elements and assess their ability to bias inheritance of an sgRNA-expressing element (kmosgRNAs). Four shu-Cas9 and one sds3-Cas9 isolines can significantly bias the inheritance of kmosgRNAs, with sds3G1-Cas9 causing the highest average inheritance of ~86% and ~94% from males and females carrying both elements outcrossed to wild-type, respectively. Our mathematical model demonstrates that sds3G1-Cas9 could enable the spread of the kmosgRNAs element to either reach a higher (by ~15 percentage point) maximum carrier frequency or to achieve similar maximum carrier frequency faster (by 12 generations) when compared to two other established split drive systems.

Dynamic Models of Within-Herd Transmission and Recommendation for Vaccination Coverage Requirement in the Case of African Swine Fever in Vietnam

African swine fever (ASF) is a highly contagious disease that is caused by the ASF virus (ASFV) with a high fatality rate in domestic pigs resulting in a high socio-economic impact. The pig business in Vietnam was recently affected by ASF for the first time. This study thus aimed to develop a disease dynamic model to explain how ASFV spreads in Vietnamese pig populations and suggest a protective vaccine coverage level required to prevent future outbreaks. The outbreak data were collected from ten private small-scale farms within the first wave of ASF outbreaks in Vietnam. Three methods were used to estimate the basic reproduction number (R₀), including the exponential growth method, maximum likelihood method, and attack rate method. The average R₀ values were estimated at 1.49 (95%CI: 1.05–2.21), 1.58 (95%CI: 0.92–2.56), and 1.46 (95%CI: 1.38–1.57), respectively. Based on the worst-case scenario, all pigs in a herd would be infected and removed within 50 days. We suggest vaccinating at least 80% of pigs on each farm once a commercially approved ASF vaccine is available. However, an improvement in biosecurity levels in small-scale farms is still greatly encouraged to prevent the introduction of the virus.

Interactions between timing and transmissibility explain diverse flavivirus dynamics in Fiji

Zika virus (ZIKV) has caused large, brief outbreaks in isolated populations, however ZIKV can also persist at low levels over multiple years. The reasons for these diverse transmission dynamics remain poorly understood. In Fiji, which has experienced multiple large single-season dengue epidemics, there was evidence of multi-year transmission of ZIKV between 2013 and 2017. To identify factors that could explain these differences in dynamics between closely related mosquito-borne flaviviruses, we jointly fit a transmission dynamic model to surveillance, serological and molecular data. We estimate that the observed dynamics of ZIKV were the result of two key factors: strong seasonal effects, which created an ecologically optimal time of year for outbreaks; and introduction of ZIKV after this optimal time, which allowed ZIKV transmission to persist over multiple seasons. The ability to jointly fit to multiple data sources could help identify a similar range of possible outbreak dynamics in other settings.

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.

Asynchronicity of endemic and emerging mosquito-borne disease outbreaks in the Dominican Republic

Mosquito-borne viruses threaten the Caribbean due to the region's tropical climate and seasonal reception of international tourists. Outbreaks of chikungunya and Zika have demonstrated the rapidity with which these viruses can spread. Concurrently, dengue fever cases have climbed over the past decade. Sustainable disease control measures are urgently needed to quell virus transmission and prevent future outbreaks. Here, to improve upon current control methods, we analyze temporal and spatial patterns of chikungunya, Zika, and dengue outbreaks reported in the Dominican Republic between 2012 and 2018. The viruses that cause these outbreaks are transmitted by Aedes mosquitoes, which are sensitive to seasonal climatological variability. We evaluate whether climate and the spatio-temporal dynamics of dengue outbreaks could explain patterns of emerging disease outbreaks. We find that emerging disease outbreaks were robust to the climatological and spatio-temporal constraints defining seasonal dengue outbreak dynamics, indicating that constant surveillance is required to prevent future health crises.

Congenital Zika syndrome: A systematic review

BACKGROUND

The signs and symptoms of Zika virus infection are usually mild and self-limited. However, the disease has been linked to neurological complications such as Guillain-Barré syndrome and peripheral nerve involvement, and also to abortion and fetal deaths due to vertical transmission, resulting in various congenital malformations in newborns, including microcephaly. This review aimed to describe the o signs and symptoms that characterize the congenital Zika syndrome.

METHODS AND FINDINGS

A systematic review was performed with a protocol and described according to the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. The search strategy yielded 2,048 studies. After the exclusion of duplicates and application of inclusion criteria, 46 studies were included. The main signs and symptoms associated with the congenital Zika syndrome were microcephaly, parenchymal or cerebellar calcifications, ventriculomegaly, central nervous system hypoplasia or atrophy, arthrogryposis, ocular findings in the posterior and anterior segments, abnormal visual function and low birthweight for gestational age.

CONCLUSIONS

Zika virus infection during pregnancy can cause a series of changes in the growth and development of children, while impacting the healthcare system due to the severity of cases. Our findings outline the disease profile in newborns and infants and may contribute to the development and updating of more specific clinical protocols.

A SIR-Poisson Model for COVID-19: Evolution and Transmission Inference in the Maghreb Central Regions

2019-nCoV is a virulent virus belonging to the coronavirus family that caused the new pneumonia (COVID-19) which has spread internationally very rapidly and has become pandemic. In this research paper, we set forward a statistical model called SIR-Poisson that predicts the evolution and the global spread of infectious diseases. The proposed SIR-Poisson model is able to predict the range of the infected cases in a future period. More precisely, it is used to infer the transmission of the COVID-19 in the three Maghreb Central countries (Tunisia, Algeria, and Morocco). Using the SIR-Poisson model and based on daily reported disease data, since its emergence until end April 2020, we attempted to predict the future disease period over 60 days. The estimated average number of contacts by an infected individual with others was around 2 for Tunisia and 3 for Algeria and Morocco. Relying on inferred scenarios, although the pandemic situation would tend to decline, it has not ended. From this perspective, the risk of COVID-19 spreading still exists after the deconfinement act. It is necessary, therefore, to carry on the containment until the estimated infected number achieves 0.

SBDiEM: A new mathematical model of infectious disease dynamics

A worldwide multi-scale interplay among a plethora of factors, ranging from micro-pathogens and individual or population interactions to macro-scale environmental, socio-economic and demographic conditions, entails the development of highly sophisticated mathematical models for robust representation of the contagious disease dynamics that would lead to the improvement of current outbreak control strategies and vaccination and prevention policies. Due to the complexity of the underlying interactions, both deterministic and stochastic epidemiological models are built upon incomplete information regarding the infectious network. Hence, rigorous mathematical epidemiology models can be utilized to combat epidemic outbreaks. We introduce a new spatiotemporal approach (SBDiEM) for modeling, forecasting and nowcasting infectious dynamics, particularly in light of recent efforts to establish a global surveillance network for combating pandemics with the use of artificial intelligence. This model can be adjusted to describe past outbreaks as well as COVID-19. Our novel methodology may have important implications for national health systems, international stakeholders and policy makers.

Effective Reproductive Number estimation for initial stage of COVID-19 pandemic in Latin American Countries

OBJECTIVES

The coronavirus disease 2019 (COVID-19) has become pandemic and turn in a challenge for Latin America. Understanding the dynamics of the epidemic is essential for decision making, and to reduce the health, economic, and social impacts of the pandemic. The present study aimed to estimate the effective reproductive number (R_t) of Severe Acute Respiratory Syndrome coronavirus 2 (SARS-Cov2) infection during the first 10 days of the outbreak in seven Latin American countries with the highest incidence of cases as of March 23, 2020. Furthermore, we chose to compare the seven countries with Spain and Italy given their history with the virus.

METHODS

Incidence data retrieved from the COVID-19 data repository by Johns Hopkins University were analyzed. The R_t was calculated for the first 10 days of the epidemic in Brazil, Ecuador, Chile, Colombia, Panama, Mexico, and Peru. R_t estimations were compared with Spain and Italy values for the same interval.

RESULTS

The median R_t for the first 10 days of the COVID-19 epidemic were 2.90 (2.67-3.14) for Spain and 2.83 (2.7-2.96) for Italy. Latin American R_t estimations were higher in Ecuador (3.95(3.7-4.21)), Panama (3.95(3.7-4.21)), and Brazil (3.95(3.7-4.21)). The smallest one was observed in Peru (2.36(2.11-2.63)). All Latin American countries had R_t greater than 2.

CONCLUSIONS

The initial stages of the COVID-19 epidemic in Latin America suggested a high Rt. Interventions such as domestic and international travel restrictions, educational institutions closure, social distancing, and intensified case surveillance should be adopted to prevent the collapse of the health systems.

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.

Age-dependent manifestations and case definitions of paediatric Zika: a prospective cohort study

BACKGROUND

Paedeatric Zika remains an understudied topic. WHO and the Pan American Health Organization (PAHO) Zika case definitions have not been assessed in children. We aimed to characterise clinical profiles and evaluate the diagnostic performance of the WHO and PAHO case definitions in a large cohort of paediatric Zika cases.

METHODS

From January, 2016 to February, 2017, encompassing the major 2016 Zika epidemic, participants in the Pediatric Dengue Cohort Study (PDCS) in Managua, Nicaragua, were encouraged to visit the study health centre at first indication of any illness. PDCS participants were aged 2-14 years, healthy at enrolment, and recruited before the initiation of the present study. Molecular and serological assays were used to test participants exhibiting any of four broad clinical profiles suspected of resulting from a symptomatic Zika virus infection. These clinical profiles were: fever and at least two of headache, retro-orbital pain, myalgia, arthralgia, rash, haemorrhagic manifestations, and leukopenia; fever and at least two of nausea or vomiting, rash, aches and pains, positive tourniquet test, leukopenia, and any dengue warning sign; undifferentiated fever without evident cause, with or without any other clinical finding; and afebrile rash with or without any other clinical finding. We characterised acute clinical findings (signs, symptoms, and complete blood counts) in both Zika cases and non-Zika cases.

FINDINGS

We prospectively followed a cohort of about 3700 children, of which 1110 were deemed eligible for inclusion. Four participants with laboratory-confirmed Zika (three co-infections with dengue virus, one missing complete blood count data) and two participants who were non-Zika cases (missing complete blood count data) were excluded from analysis. We analysed 556 laboratory-confirmed Zika and 548 non-Zika cases. The WHO case definition captured 176 confirmed Zika cases, and the PAHO definition 109 confirmed Zika cases, who presented with the most clinical findings and a dengue-like clinical profile. The remaining two thirds of Zika cases, principally characterised by undifferentiated fever or afebrile rash, were missed. Among Zika cases, rash (n=440)-particularly generalised erythematous rash (n=334)-fever (n=333), leukopenia (n=217), and headache (n=203) were most common and peaked within 3 days of illness onset. The most common Zika presentation over the first week of illness was rash only (n=80). The sensitivity of Zika case definitions increased across paediatric age (from 11·3% to 56·1% for the WHO case definition and from 6·0% to 36·6% for the PAHO case definition), as the prevalence of most clinical findings (particularly arthralgia) increased with age, irrespective of previous dengue virus infection. Consequently, Zika manifested differently across paediatric age; older Zika cases presented with a dengue-like clinical profile while younger Zika cases presented with undifferentiated fever or afebrile rash.

INTERPRETATION

We provide the most thorough description of paediatric Zika to date. Most paediatric Zika cases go undetected under the WHO and PAHO case definitions, suggesting that current standards for Zika case ascertainment require revision. Zika manifests with mild but differing clinical profiles across paediatric age, presenting major challenges to diagnosis, surveillance, and efforts to control future Zika epidemics.

FUNDING

US National Institutes of Health.

Spatial Dynamics of Chikungunya Virus, Venezuela, 2014

Since chikungunya virus emerged in the Caribbean region in late 2013, ≈45 countries have experienced chikungunya outbreaks. We described and quantified the spatial and temporal events after the introduction and propagation of chikungunya into an immunologically naive population from the urban north-central region of Venezuela during 2014. The epidemic curve (n = 810 cases) unraveled within 5 months with a basic reproductive number of 3.7 and a radial spread traveled distance of 9.4 km at a mean velocity of 82.9 m/day. The highest disease diffusion speed occurred during the first 90 days, and space and space-time modeling suggest the epidemic followed a particular geographic pathway with spatiotemporal aggregation. The directionality and heterogeneity of transmission during the first introduction of chikungunya indicated existence of areas of diffusion and elevated risk for disease and highlight the importance of epidemic preparedness. This information will help in managing future threats of new or reemerging arboviruses.

Transmission Dynamics and Control Mechanisms of Vector-Borne Diseases with Active and Passive Movements Between Urban and Satellite Cities

A metapopulation model which explicitly integrates vector-borne and sexual transmission of an epidemic disease with passive and active movements between an urban city and a satellite city is formulated and analysed. The basic reproduction number of the disease is explicitly determined as a combination of sexual and vector-borne transmission parameters. The sensitivity analysis reveals that the disease is primarily transmitted via the vector-borne mode, rather than via sexual transmission, and that sexual transmission by itself may not initiate or sustain an outbreak. Also, increasing the population movements from one city to the other leads to an increase in the basic reproduction number of the later city but a decrease in the basic reproduction number of the former city. The influence of other significant parameters is also investigated via the analysis of suitable partial rank correlation coefficients. After gauging the effects of mobility, we explore the potential effects of optimal control strategies relying upon several distinct restrictions on population movement.

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.

Epidemic potential of Zika virus in Australia: implications for blood transfusion safety

BACKGROUND

Zika virus (ZIKV) is transfusion-transmissible. In Australia the primary vector, Aedes aegypti, is established in the north-east, such that local transmission is possible following importation of an index case, which has the potential to impact on blood transfusion safety and public health. We estimated the basic reproduction number (R ₀ ) to model the epidemic potential of ZIKV in Australian locations, compared this with the ecologically similar dengue viruses (DENV), and examined possible implications for blood transfusion safety.

STUDY DESIGN AND METHODS

Varying estimates of vector control efficiency and extrinsic incubation period, "best-case" and "worst-case" scenarios of monthly R ₀ for ZIKV and DENV were modeled from 1996 to 2015 in 11 areas. We visualized the geographical distribution of blood donors in relation to areas with epidemic potential for ZIKV.

RESULTS

Epidemic potential (R ₀ > 1) existed for ZIKV and DENV throughout the study period in a number of locations in northern Australia (Cairns, Darwin, Rockhampton, Thursday Island, Townsville, and Brisbane) during the warmer months of the year. R ₀ for DENV was greater than ZIKV and was broadly consistent with annual estimates in Cairns. Increased vector control efficiency markedly reduced the epidemic potential and shortened the season of local transmission. Australian locations that provide the greatest number of blood donors did not have epidemic potential for ZIKV.

CONCLUSION

We estimate that areas of north-eastern Australia could sustain local transmission of ZIKV. This early contribution to understanding the epidemic potential of ZIKV may assist in the assessment and management of threats to blood transfusion safety.

Reassessing Serosurvey-Based Estimates of the Symptomatic Proportion of Zika Virus Infections

Since the 2007 Zika epidemic in the Micronesian state of Yap, it has been apparent that not all people infected with Zika virus (ZIKV) experience symptoms. However, the proportion of infections that result in symptoms remains unclear. Existing estimates have varied in their interpretation of symptoms due to other causes and the case definition used, and they have assumed perfect test sensitivity and specificity. Using a Bayesian model and data from ZIKV serosurveys in Yap (2007), French Polynesia (2013-2014), and Puerto Rico (2016), we found that assuming perfect sensitivity and specificity generally led to lower estimates of the symptomatic proportion. Incorporating reasonable assumptions for assay sensitivity and specificity, we estimated that 27% (95% credible interval (CrI): 15, 37) (Yap), 44% (95% CrI: 26, 66) (French Polynesia), and 50% (95% CrI: 34, 92) (Puerto Rico) of infections were symptomatic, with variation due to differences in study populations, study designs, and case definitions. The proportion of ZIKV infections causing symptoms is critical for surveillance system design and impact assessment. Here, we accounted for key uncertainties in existing seroprevalence data and found that estimates for the symptomatic proportion ranged from 27% to 50%, suggesting that while the majority of infections are asymptomatic or mildly symptomatic, symptomatic infections might be more common than previously estimated.

Prior dengue virus infection and risk of Zika: A pediatric cohort in Nicaragua

BACKGROUND

Zika virus (ZIKV) emerged in northeast Brazil in 2015 and spread rapidly across the Americas, in populations that have been largely exposed to dengue virus (DENV). The impact of prior DENV infection on ZIKV infection outcome remains unclear. To study this potential impact, we analyzed the large 2016 Zika epidemic in Managua, Nicaragua, in a pediatric cohort with well-characterized DENV infection histories.

METHODS AND FINDINGS

Symptomatic ZIKV infections (Zika cases) were identified by real-time reverse transcription PCR and serology in a community-based cohort study that follows approximately 3,700 children aged 2-14 years old. Annual blood samples were used to identify clinically inapparent ZIKV infections using a novel, well-characterized serological assay. Multivariable Poisson regression was used to examine the relation between prior DENV infection and incidence of symptomatic and inapparent ZIKV infection. The generalized-growth method was used to estimate the effective reproduction number. From January 1, 2016, to February 28, 2017, 560 symptomatic ZIKV infections and 1,356 total ZIKV infections (symptomatic and inapparent) were identified, for an overall incidence of 14.0 symptomatic infections (95% CI: 12.9, 15.2) and 36.5 total infections (95% CI: 34.7, 38.6) per 100 person-years. Effective reproduction number estimates ranged from 3.3 to 3.4, depending on the ascending wave period. Incidence of symptomatic and total ZIKV infections was higher in females and older children. Analysis of the effect of prior DENV infection was performed on 3,027 participants with documented DENV infection histories, of which 743 (24.5%) had experienced at least 1 prior DENV infection during cohort follow-up. Prior DENV infection was inversely associated with risk of symptomatic ZIKV infection in the total cohort population (incidence rate ratio [IRR]: 0.63; 95% CI: 0.48, 0.81; p < 0.005) and with risk of symptomatic presentation given ZIKV infection (IRR: 0.62; 95% CI: 0.44, 0.86) when adjusted for age, sex, and recent DENV infection (1-2 years before ZIKV infection). Recent DENV infection was significantly associated with decreased risk of symptomatic ZIKV infection when adjusted for age and sex, but not when adjusted for prior DENV infection. Prior or recent DENV infection did not affect the rate of total ZIKV infections. Our findings are limited to a pediatric population and constrained by the epidemiology of the site.

CONCLUSIONS

These findings support that prior DENV infection may protect individuals from symptomatic Zika. More research is needed to address the possible immunological mechanism(s) of cross-protection between ZIKV and DENV and whether DENV immunity also modulates other ZIKV infection outcomes such as neurological or congenital syndromes.

Uncertainty and sensitivity analysis of the basic reproduction number of diphtheria: a case study of a Rohingya refugee camp in Bangladesh, November-December 2017

Background

A Rohingya refugee camp in Cox's Bazar, Bangladesh experienced a large-scale diphtheria epidemic in 2017. The background information of previously immune fraction among refugees cannot be explicitly estimated, and thus we conducted an uncertainty analysis of the basic reproduction number, R₀.

Methods

A renewal process model was devised to estimate the R₀ and ascertainment rate of cases, and loss of susceptible individuals was modeled as one minus the sum of initially immune fraction and the fraction naturally infected during the epidemic. To account for the uncertainty of initially immune fraction, we employed a Latin Hypercube sampling (LHS) method.

Results

R₀ ranged from 4.7 to 14.8 with the median estimate at 7.2. R₀ was positively correlated with ascertainment rates. Sensitivity analysis indicated that R₀ would become smaller with greater variance of the generation time.

Discussion

Estimated R₀ was broadly consistent with published estimate from endemic data, indicating that the vaccination coverage of 86% has to be satisfied to prevent the epidemic by means of mass vaccination. LHS was particularly useful in the setting of a refugee camp in which the background health status is poorly quantified.

Dynamics of Zika virus outbreaks: an overview of mathematical modeling approaches

BACKGROUND

The Zika virus was first discovered in 1947. It was neglected until a major outbreak occurred on Yap Island, Micronesia, in 2007. Teratogenic effects resulting in microcephaly in newborn infants is the greatest public health threat. In 2016, the Zika virus epidemic was declared as a Public Health Emergency of International Concern (PHEIC). Consequently, mathematical models were constructed to explicitly elucidate related transmission dynamics.

SURVEY METHODOLOGY

In this review article, two steps of journal article searching were performed. First, we attempted to identify mathematical models previously applied to the study of vector-borne diseases using the search terms "dynamics," "mathematical model," "modeling," and "vector-borne" together with the names of vector-borne diseases including chikungunya, dengue, malaria, West Nile, and Zika. Then the identified types of model were further investigated. Second, we narrowed down our survey to focus on only Zika virus research. The terms we searched for were "compartmental," "spatial," "metapopulation," "network," "individual-based," "agent-based" AND "Zika." All relevant studies were included regardless of the year of publication. We have collected research articles that were published before August 2017 based on our search criteria. In this publication survey, we explored the Google Scholar and PubMed databases.

RESULTS

We found five basic model architectures previously applied to vector-borne virus studies, particularly in Zika virus simulations. These include compartmental, spatial, metapopulation, network, and individual-based models. We found that Zika models carried out for early epidemics were mostly fit into compartmental structures and were less complicated compared to the more recent ones. Simple models are still commonly used for the timely assessment of epidemics. Nevertheless, due to the availability of large-scale real-world data and computational power, recently there has been growing interest in more complex modeling frameworks.

DISCUSSION

Mathematical models are employed to explore and predict how an infectious disease spreads in the real world, evaluate the disease importation risk, and assess the effectiveness of intervention strategies. As the trends in modeling of infectious diseases have been shifting towards data-driven approaches, simple and complex models should be exploited differently. Simple models can be produced in a timely fashion to provide an estimation of the possible impacts. In contrast, complex models integrating real-world data require more time to develop but are far more realistic. The preparation of complicated modeling frameworks prior to the outbreaks is recommended, including the case of future Zika epidemic preparation.

Effects of contact network structure on epidemic transmission trees: implications for data required to estimate network structure

Understanding the dynamics of disease spread is key to developing effective interventions to control or prevent an epidemic. The structure of the network of contacts over which the disease spreads has been shown to have a strong influence on the outcome of the epidemic, but an open question remains as to whether it is possible to estimate contact network features from data collected in an epidemic. The approach taken in this paper is to examine the distributions of epidemic outcomes arising from epidemics on networks with particular structural features to assess whether that structure could be measured from epidemic data and what other constraints might be needed to make the problem identifiable. To this end, we vary the network size, mean degree, and transmissibility of the pathogen, as well as the network feature of interest: clustering, degree assortativity, or attribute-based preferential mixing. We record several standard measures of the size and spread of the epidemic, as well as measures that describe the shape of the transmission tree in order to ascertain whether there are detectable signals in the final data from the outbreak. The results suggest that there is potential to estimate contact network features from transmission trees or pure epidemic data, particularly for diseases with high transmissibility or for which the relevant contact network is of low mean degree. Copyright © 2017 John Wiley & Sons, Ltd.

Advances in Diagnosis, Surveillance, and Monitoring of Zika Virus: An Update

Zika virus (ZIKV) is associated with numerous human health-related disorders, including fetal microcephaly, neurological signs, and autoimmune disorders such as Guillain-Barré syndrome (GBS). Perceiving the ZIKA associated losses, in 2016, the World Health Organization (WHO) declared it as a global public health emergency. In consequence, an upsurge in the research on ZIKV was seen around the globe, with significant attainments over developing several effective diagnostics, drugs, therapies, and vaccines countering this life-threatening virus at an early step. State-of-art tools developed led the researchers to explore virus at the molecular level, and in-depth epidemiological investigations to understand the reason for increased pathogenicity and different clinical manifestations. These days, ZIKV infection is diagnosed based on clinical manifestations, along with serological and molecular detection tools. As, isolation of ZIKV is a tedious task; molecular assays such as reverse transcription-polymerase chain reaction (RT-PCR), real-time qRT-PCR, loop-mediated isothermal amplification (LAMP), lateral flow assays (LFAs), biosensors, nucleic acid sequence-based amplification (NASBA) tests, strand invasion-based amplification tests and immune assays like enzyme-linked immunosorbent assay (ELISA) are in-use to ascertain the ZIKV infection or Zika fever. Herein, this review highlights the recent advances in the diagnosis, surveillance, and monitoring of ZIKV. These new insights gained from the recent advances can aid in the rapid and definitive detection of this virus and/or Zika fever. The summarized information will aid the strategies to design and adopt effective prevention and control strategies to counter this viral pathogen of great public health concern.

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 theoretical model for Zika virus transmission

In this paper, we present and analyze an SEIR Zika epidemic model. Firstly, we investigate the model with constant controls. The steady states of the model is found to be locally and globally asymptotically stable. Thereafter, we incorporate time dependent controls into the model in order to investigate the optimal effects of bednets, treatments of infective and spray of insecticides on the disease spread. Furthermore, we used Pontryagin’s Maximum Principle to determine the necessary conditions for effective control of the disease. Also, the numerical results were presented.

Epidemiological and ecological determinants of Zika virus transmission in an urban setting

The Zika virus has emerged as a global public health concern. Its rapid geographic expansion is attributed to the success of Aedes mosquito vectors, but local epidemiological drivers are still poorly understood. Feira de Santana played a pivotal role in the Chikungunya epidemic in Brazil and was one of the first urban centres to report Zika infections. Using a climate-driven transmission model and notified Zika case data, we show that a low observation rate and high vectorial capacity translated into a significant attack rate during the 2015 outbreak, with a subsequent decline in 2016 and fade-out in 2017 due to herd-immunity. We find a potential Zika-related, low risk for microcephaly per pregnancy, but with significant public health impact given high attack rates. The balance between the loss of herd-immunity and viral re-importation will dictate future transmission potential of Zika in this urban setting.

Mosquitoes can transmit viruses that cause Zika, dengue and several other tropical diseases that affect humans. Zika virus usually causes mild symptoms, but it is thought that infection during pregnancy can lead to brain abnormalities, including microcephaly, where babies are born with an abnormally small head. Recent studies have shed light on how the Zika virus spread from Africa to reach South America, the Caribbean and North America. However, much less is known about the ecological factors that contribute to the spread of the virus within towns, cities and other local areas.

In 2015, Brazil was struck by an outbreak of the Zika virus that led to an international public health emergency. Lourenço et al. used a mathematical model to explore the local conditions within Feira de Santana (a major urban center in Brazil) that contributed to the outbreak. The model took into account numerous factors, including temperature, humidity, rainfall and the mosquito life-cycle, which made it possible to reconstruct the history of the virus over the past three years and to make projections for the next decades.

It revealed that most of the infections occured during 2015, with approximately 65% of the population infected. The incidences of new infections declined in 2016, as increasing numbers of local people had already been exposed to the virus and became immune. Temperature and humidity appeared to have played a critical role in sustaining the mosquito population carrying the Zika virus.

Further analysis suggests that the risk of Zika virus causing microcephaly is very low – only 0.3–0.5% of the pregnant women in Feira de Santana who were infected with Zika gave birth to a baby with the condition. What therefore makes Zika a public health concern is the combination of a low risk with very high infection rates, which can affect a large number of pregnancies.

This study will help researchers and policy makers to predict how the Zika virus will behave in the coming years. It also highlights the limitations and successes of the current system of surveillance. Moreover, it will help to identify critical time periods in the year when mosquito control strategies should be implemented to limit the spread of this virus. In future, this could help shape new local strategies to control Zika virus, dengue and other diseases carried by mosquitoes.

Macaque monkeys in Zika virus research: 1947-present

Zika virus was first isolated in 1947 from an exotic rhesus macaque. Nearly 70 years later, the emergence of Zika virus in the Americas and its newly described association with birth defects has motivated the development of captive macaque monkey models of human Zika virus infection. This review describes similarities between macaque and human Zika virus pathogenesis and discusses specific advantages and disadvantages of using macaques instead of other laboratory animal models. In particular, macaques provide an outstanding model for understanding in utero Zika virus infections that are essential for evaluating preclinical interventions for use in pregnancy.

Outbreak of Zika virus infection in Singapore: an epidemiological, entomological, virological, and clinical analysis

BACKGROUND

An outbreak of Zika virus infection was detected in Singapore in August, 2016. We report the first comprehensive analysis of a national response to an outbreak of Zika virus infection in Asia.

METHODS

In the first phase of the outbreak, patients with suspected Zika virus infection were isolated in two national referral hospitals until their serum tested negative for the virus. Enhanced vector control and community engagement measures were deployed in disease clusters, including stepped-up mosquito larvicide and adulticide use, community participation in source reduction (destruction of mosquito breeding sites), and work with the local media to promote awareness of the outbreak. Clinical and epidemiological data were collected from patients with confirmed Zika virus infection during the first phase. In the second phase, admission into hospitals for isolation was stopped but vector control efforts continued. Mosquitoes were captured from areas with Zika disease clusters to assess which species were present, their breeding numbers, and to test for Zika virus. Mosquito virus strains were compared with human strains through phylogenetic analysis after full genome sequencing. Reproductive numbers and inferred dates of strain diversification were estimated through Bayesian analyses.

FINDINGS

From Aug 27 to Nov 30, 2016, 455 cases of Zika virus infection were confirmed in Singapore. Of 163 patients with confirmed Zika virus infection who presented to national referral hospitals during the first phase of the outbreak, Zika virus was detected in the blood samples of 97 (60%) patients and the urine samples of 157 (96%) patients. There were 15 disease clusters, 12 of which had high Aedes aegypti breeding percentages. Captured mosquitoes were pooled into 517 pools for Zika virus screening; nine abdomen pools (2%) were positive for Zika virus, of which seven head and thorax pools were Zika-virus positive. In the phylogenetic analysis, all mosquito sequences clustered within the outbreak lineage. The lineage showed little diversity and was distinct from other Asian lineages. The estimated most recent common ancestor of the outbreak lineage was from May, 2016. With the deployment of vector control and community engagement measures, the estimated reproductive number fell from 3·62 (95% CI 3·48-3·77) for July 31 to Sept 1, 2016, to 1·22 (95% CI 1·19-1·24) 4 weeks later (Sept 1 to Nov 24, 2016).

INTERPRETATION

The outbreak shows the ease with which Zika virus can be introduced and spread despite good baseline vector control. Disease surveillance, enhanced vector control, and community awareness and engagement helped to quickly curb further spread of the virus. These intensive measures might be useful for other countries facing the same threat.

FUNDING

National Medical Research Council Singapore, Centre for Infectious Disease Epidemiology and Research, and A*STAR Biomedical Research Council.

An integrated approach for the assessment of the Aedes aegypti and Aedes albopictus global spatial distribution, and determination of the zones susceptible to the development of Zika virus

The Zika virus, one of the new epidemic diseases, is reported to have affected millions of people in the past year. The suitable climate conditions of the areas where Zika virus has been reported, especially in areas with a high population density, are the main cause of the current outbreak and spread of the disease. Indeed, the suitable climatic conditions of certain territories constitute perfect breading nest for the propagation and outbreak of worldwide diseases. The main objective of this research is to analyze the global distribution and predicted areas of both mosquitoes Ae. aegypti and Ae. albopictus which are the main vectors of Zika virus. Physical (SRTM) and climatic variables (WorldClim) were used to obtain the susceptibility maps based on the optimum conditions for the development of these mosquitoes. The susceptibility model was developed using a Species Distribution Model - correlative model, namely the Maximum Entropy, that used as input the spatial references of both vectors (Dryad Digital Repository). The results show the most important classes of each independent variable used in assessing the presence of each species of mosquitoes and the areas susceptible to the presence of these vector species. It turns out that Ae. aegypti has greater global dispersion than the Ae. albopictus specie, although two common regions stand out as the most prone to the presence of both mosquito species (tropical and subtropical zones). The crossing of these areas of greater susceptibility with areas of greater population density (e.g. India, China, Se of USA and Brazil) shows some agreement, and these areas stand out due to the presence of several records of Zika virus (HealthMap Project). In this sense, through the intersection of susceptibility and human exposure the areas with increased risk of development and spread of Zika virus are pinpointed, suggesting that there may be a new outbreak of this virus in these places, if preventive measures are not adopted.

Host-Virus Interaction of ZIKA Virus in Modulating Disease Pathogenesis

The Zika virus (ZIKV) is a newly emerging pathogen that has resulted in a worldwide epidemic. It primarily spreads either through infected Aedes aegypti or Aedes albopictus mosquitos leading to severe neurological disorders such as microcephaly and Guillain-Barré syndrome in susceptible individuals. The mode of ZIKV entry into specific cell types such as: epidermal keratinocytes, fibroblasts, immature dendritic cells (iDCs), and stem-cell-derived human neural progenitors has been determined through its major surface envelope glycoprotein. It has been known that oligosaccharides that are covalently linked to viral envelope proteins are crucial in defining host-virus interactions. However, the role of sugars/glycans in exploiting host-immune mechanisms and aiding receptor-mediated virus entry is not well defined. Therefore, this review focuses on host-pathogen interactions to better understand ZIKV pathogenesis.

Temporal patterns and geographic heterogeneity of Zika virus (ZIKV) outbreaks in French Polynesia and Central America

BACKGROUND

Zika virus (ZIKV) transmission has been reported in 67 countries/territories in the Oceania region and the Americas since 2015, prompting the World Health Organization (WHO) to declare ZIKV as a Public Health Emergency of International Concern in February 2016, due to its strong association with medical complications such as microcephaly and Guillain-Barré Syndrome (GBS). However, a substantial gap in knowledge still exists regarding differing temporal pattern and potential of transmission of ZIKV in different regions of the world.

METHODS

We use a phenomenological model to ascertain the temporal patterns and transmission potential of ZIKV in various countries/territories, by fitting the model to Zika case data from Yap Island and French Polynesia in the Oceania region and 11 countries/territories with confirmed case data, namely, Colombia, Ecuador, French Guiana, Guadeloupe, Guatemala, Mexico, Nicaragua, Panama, Puerto Rico, Saint Martin, and Suriname, to pinpoint the waves of infections in each country/territory and to estimate the respective basic reproduction number R₀.

RESULTS

Six of these time series datasets resulted in statistically significant model fit of at least one wave of reported cases, namely that of French Polynesia, Colombia, Puerto Rico, Guatemala, Suriname and Saint Martin. However, only Colombia and Guatemala exhibited two waves of cases while the others had only one wave. Temporal patterns of the second wave in Colombia and the single wave in Suriname are very similar, with the respective turning points separated by merely a week. Moreover, the mean estimates of R₀ for Colombia, Guatemala and Suriname, all land-based populations, range between 1.05 and 1.75, while the corresponding mean estimates for R₀ of island populations in French Polynesia, Puerto Rico and Saint Martin are significantly lower with a range of 5.70-6.89. We also fit the Richards model to Zika case data from six main archipelagos in French Polynesia, suggesting the outbreak in all six island populations occurred during the same time, albeit with different peak time, with mean R₀ range of 3.09-5.05.

DISCUSSION

Using the same modeling methodology, in this study we found a significant difference between transmissibility (as quantified by R₀) in island populations as opposed to land-based countries/territories, possibly suggesting an important role of geographic heterogeneity in the spread of vector-borne diseases and its future course, which requires further monitoring. Our result has potential implications for planning respective intervention and control policies targeted for island and land-based populations.

Zika in Rio de Janeiro: Assessment of basic reproduction number and comparison with dengue outbreaks

Zika virus infection was declared a public health emergency of international concern in February 2016 in response to the outbreak in Brazil and its suspected link with congenital anomalies. In this study, we use notification data and disease natural history parameters to estimate the basic reproduction number (R 0) of Zika in Rio de Janeiro, Brazil. We also obtain estimates of R 0 of dengue from time series of dengue cases in the outbreaks registered in 2002 and 2012 in the city, when DENV-3 and DENV-4 serotypes, respectively, had just emerged. Our estimates of the basic reproduction number for Zika in Rio de Janeiro based on surveillance notifications (R 0 = 2·33, 95% CI: 1·97-2·97) were higher than those obtained for dengue in the city (year 2002: R 0 = 1·70 [1·50-2·02]; year 2012: R 0 = 1·25 [1·18-1·36]). Given the role of Aedes aegypti as vector of both the Zika and dengue viruses, we also derive R 0 of Zika as a function of both dengue reproduction number and entomological and epidemiological parameters for dengue and Zika. Using the dengue outbreaks from previous years allowed us to estimate the potential R 0 of Zika. Our estimates were closely in agreement with our first Zika's R 0 estimation from notification data. Hence, these results validate deriving the potential risk of Zika transmission in areas with recurring dengue outbreaks. Whether transmission routes other than vector-based can sustain a Zika epidemic still deserves attention, but our results suggest that the Zika outbreak in Rio de Janeiro emerged due to population susceptibility and ubiquitous presence of Ae. aegypti.

A comparative analysis of Chikungunya and Zika transmission

The recent global dissemination of Chikungunya and Zika has fostered public health concern worldwide. To better understand the drivers of transmission of these two arboviral diseases, we propose a joint analysis of Chikungunya and Zika epidemics in the same territories, taking into account the common epidemiological features of the epidemics: transmitted by the same vector, in the same environments, and observed by the same surveillance systems. We analyse eighteen outbreaks in French Polynesia and the French West Indies using a hierarchical time-dependent SIR model accounting for the effect of virus, location and weather on transmission, and based on a disease specific serial interval. We show that Chikungunya and Zika have similar transmission potential in the same territories (transmissibility ratio between Zika and Chikungunya of 1.04 [95% credible interval: 0.97; 1.13]), but that detection and reporting rates were different (around 19% for Zika and 40% for Chikungunya). Temperature variations between 22°C and 29°C did not alter transmission, but increased precipitation showed a dual effect, first reducing transmission after a two-week delay, then increasing it around five weeks later. The present study provides valuable information for risk assessment and introduces a modelling framework for the comparative analysis of arboviral infections that can be extended to other viruses and territories.

A comprehensive analysis and immunobiology of autoimmune neurological syndromes during the Zika virus outbreak in Cúcuta, Colombia

We have focused on the epidemiology and immunobiology of Zika virus (ZIKV) infection and factors associated with the development of Guillain-Barré syndrome (GBS) and other neurological syndromes in Cúcuta, the capital of North Santander department, Colombia. Data of patients with ZIKV disease reported to the national population-based surveillance system were used to calculate the basic reproduction number (R₀) and the attack rates (ARs) as well as to develop epidemiological maps. Patients with neurological syndromes were contacted and their diagnoses were confirmed. A case-control study in which 29 patients with GBS associated with ZIKV compared with 74-matched control patients with ZIKV infection alone was undertaken. Antibodies against arboviruses and other infections that may trigger GBS were evaluated. The estimated value of R₀ ranged between 2.68 (95% CI 2.54-2.67) to 4.57 (95% CI 4.18-5.01). The sex-specific ARs were 1306 per 100,000 females, and 552 per 100,000 males. A non-linear interaction between age and gender on the ARs was observed. The incidence of GBS in Cúcuta increased 4.41 times secondary to ZIKV infection. The lag time between ZIKV infection and neurological symptoms was 7 days (interquartile range 2-14.5). Patients with GBS appeared to represent a lower socioeconomic status and were living near to environmentally contaminated areas. All GBS patients were positive for IgG antibodies against both ZIKV and Dengue virus, and 69% were positive for Chikungunya virus. Noteworthy, GBS was associated with a previous infection with M. pneumoniae (OR: 3.95; 95% CI 1.44-13.01; p = 0.006). No differences in antibody levels against C. jejuni, Epstein-Barr virus and cytomegalovirus were observed. High rates of cranial nerves involvement and dysautonomia were present in 82% and 75.9%, respectively. Intensive care unit (ICU) admission was necessary in 69% of the GBS patients. Most of the patients disclosed a high disability condition (Hughes grade 4). Dysautonomia was the main risk factor of poor GBS prognosis (i.e., ICU admission and disability). Thirteen patients were diagnosed with other neurological syndromes different to GBS (6 with transverse myelitis, 3 with encephalitis, 3 with peripheral facial palsy and one with thoraco-lumbosacral myelopathy). Our data confirm an increased transmission of ZIKV in Cúcuta, and provide support to the view that severe neurological syndromes are related to ZIKV disease. The complex ways by which previous infections and socioeconomic status interact to increase the risk of GBS in people infected by ZIKV should be further investigated.

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

The recent spread of mosquito-transmitted viruses and associated disease to the Americas motivates a new, data-driven evaluation of risk in temperate population centers. Temperate regions are generally expected to pose low risk for significant mosquito-borne disease; however, the spread of the Asian tiger mosquito (Aedes albopictus) across densely populated urban areas has established a new landscape of risk. We use a model informed by field data to assess the conditions likely to facilitate local transmission of chikungunya and Zika viruses from an infected traveler to Ae. albopictus and then to other humans in USA cities with variable human densities and seasonality. Mosquito-borne disease occurs when specific combinations of conditions maximize virus-to-mosquito and mosquito-to-human contact rates. We develop a mathematical model that captures the epidemiology and is informed by current data on vector ecology from urban sites. The model demonstrates that under specific but realistic conditions, fifty-percent of introductions by infectious travelers to a high human, high mosquito density city could initiate local transmission and 10% of the introductions could result in 100 or more people infected. Despite the propensity for Ae. albopictus to bite non-human vertebrates, we also demonstrate that local virus transmission and human outbreaks may occur when vectors feed from humans even just 40% of the time. Inclusion of human behavioral changes and mitigations were not incorporated into the models and would likely reduce predicted infections. This work demonstrates how a conditional series of non-average events can result in local arbovirus transmission and outbreaks of human disease, even in temperate cities.

Comparative Analysis of Dengue and Zika Outbreaks Reveals Differences by Setting and Virus

The pacific islands of Micronesia have experienced several outbreaks of mosquito-borne diseases over the past decade. In outbreaks on small islands, the susceptible population is usually well defined, and there is no co-circulation of pathogens. Because of this, analysing such outbreaks can be useful for understanding the transmission dynamics of the pathogens involved, and particularly so for yet understudied pathogens such as Zika virus. Here, we compared three outbreaks of dengue and Zika virus in two different island settings in Micronesia, the Yap Main Islands and Fais, using a mathematical model of transmission dynamics and making full use of commonalities in disease and setting between the outbreaks. We found that the estimated reproduction numbers for Zika and dengue were similar when considered in the same setting, but that, conversely, reproduction number for the same disease can vary considerably by setting. On the Yap Main Islands, we estimated a reproduction number of 8.0-16 (95% Credible Interval (CI)) for the dengue outbreak and 4.8-14 (95% CI) for the Zika outbreak, whereas for the dengue outbreak on Fais our estimate was 28-102 (95% CI). We further found that the proportion of cases of Zika reported was smaller (95% CI 1.4%-1.9%) than that of dengue (95% CI: 47%-61%). We confirmed these results in extensive sensitivity analysis. They suggest that models for dengue transmission can be useful for estimating the predicted dynamics of Zika transmission, but care must be taken when extrapolating findings from one setting to another.

Structure in the variability of the basic reproductive number (R0) for Zika epidemics in the Pacific islands

Before the outbreak that reached the Americas in 2015, Zika virus (ZIKV) circulated in Asia and the Pacific: these past epidemics can be highly informative on the key parameters driving virus transmission, such as the basic reproduction number (R0). We compare two compartmental models with different mosquito representations, using surveillance and seroprevalence data for several ZIKV outbreaks in Pacific islands (Yap, Micronesia 2007, Tahiti and Moorea, French Polynesia 2013-2014, New Caledonia 2014). Models are estimated in a stochastic framework with recent Bayesian techniques. R0 for the Pacific ZIKV epidemics is estimated between 1.5 and 4.1, the smallest islands displaying higher and more variable values. This relatively low range of R0 suggests that intervention strategies developed for other flaviviruses should enable as, if not more effective control of ZIKV. Our study also highlights the importance of seroprevalence data for precise quantitative analysis of pathogen propagation, to design prevention and control strategies.

DOI:http://dx.doi.org/10.7554/eLife.19874.001

Zika virus is an infectious disease primarily transmitted between people by mosquitoes. While most people develop mild flu-like symptoms, infection during pregnancy can interfere with how the baby’s head and brain develop. Until recently, the virus had only been seen sporadically in Africa and Asia, but since 2007, outbreaks have been recorded on several Pacific islands. In 2015, the Zika virus reached the Americas, and within six months over 1.5 million cases had been reported in Brazil alone.

There is an urgent need to understand how the Zika virus moves within a population in order to help policymakers, and public health professionals, plan treatment and control of outbreaks of the disease. Researchers often use predictive models to estimate how a disease will spread. A parameter commonly calculated by these models is the “basic reproductive number”, or R₀, which represents the average number of additional cases of the disease caused by one infected individual.

Using models that incorporated data from Zika virus outbreaks that occurred on several Pacific islands, Champagne et al. have produced estimates of R₀ that range from 1.5-4.1.

The R₀ values are greater than one, indicating that infection will spread within a population, but in the same range as those obtained for dengue fever, another closely related mosquito-borne disease. This suggests that by taking appropriate measures, the spread of Zika and dengue can be controlled to similar extents.

A closer look at the relationship between the population size and the predicted R₀ value for each Pacific island revealed an unexpected inverse relationship: the smaller the population, the larger the value of R₀. Since other regional factors may also explain these large differences between settings, further work is needed to disentangle context-specific from disease-specific factors. In this respect, data about seroprevalence (the number of people whose blood shows evidence of a past infection) in different populations is crucial for precisely analyzing the spread of Zika virus.

DOI:http://dx.doi.org/10.7554/eLife.19874.002

Zika Virus Causes Testis Damage and Leads to Male Infertility in Mice

Zika virus (ZIKV) persists in the semen of male patients, a first for flavivirus infection. Here, we demonstrate that ZIKV can induce inflammation in the testis and epididymidis, but not in the prostate or seminal vesicle, and can lead to damaged testes after 60 days post-infection in mice. ZIKV induces innate immune responses in Leydig, Sertoli, and epididymal epithelial cells, resulting in the production of pro-inflammatory cytokines/chemokines. However, ZIKV does not induce a rapid and abundant cytokine production in peritubular cell and spermatogonia, suggesting that these cells are vulnerable for ZIKV infection and could be the potential repositories for ZIKV. Our study demonstrates a correlation between ZIKV and testis infection/damage and suggests that ZIKV infection, under certain circumstances, can eventually lead to male infertility.

Estimating the subcritical transmissibility of the Zika outbreak in the State of Florida, USA, 2016

BACKGROUND

Florida State has reported autochthonous transmission of Zika virus since late July 2016. Here we assessed the transmissibility associated with the outbreak and generated a short-term forecast.

METHODS

Time-dependent dynamics of imported cases reported in the state of Florida was approximated by a logistic growth equation. We estimated the reproduction number using the renewal equation in order to predict the incidence of local cases arising from both local and imported primary cases. Using a bootstrap method together with the logistic and renewal equations, a short-term forecast of local and imported cases was carried out.

RESULTS

The reproduction number was estimated at 0.16 (95 % Confidence Interval: 0.13, 0.19). Employing the logistic equation to capture a drastic decline in the number of imported cases expected through the course of 2016, together with the low estimate of the local reproduction number in Florida, the expected number of local reported cases was demonstrated to show an evident declining trend for the remainder of 2016.

CONCLUSIONS

The risk of local transmission in the state of Florida is predicted to dramatically decline by the end of 2016.

Implication of vaccination against dengue for Zika outbreak

Zika virus co-circulates with dengue in tropical and sub-tropical regions. Cases of co-infection by dengue and Zika have been reported, the implication of this co-infection for an integrated intervention program for controlling both dengue and Zika must be addressed urgently. Here, we formulate a mathematical model to describe the transmission dynamics of co-infection of dengue and Zika with particular focus on the effects of Zika outbreak by vaccination against dengue among human hosts. Our analysis determines specific conditions under which vaccination against dengue can significantly increase the Zika outbreak peak, and speed up the Zika outbreak peak timing. Our results call for further study about the co-infection to direct an integrated control to balance the benefits for dengue control and the damages of Zika outbreak.

Ecological effects on arbovirus-mosquito cycles of transmission

Mosquitoes transmit many viruses to a variety of hosts. Cycles of mosquito borne arbovirus transmission are the result of complex interactions between the mosquito, the arbovirus and the host that are influenced by genetic variations in a variety of traits in each that are all influenced by many environmental factors. R₀, the basic reproduction number or mean number of individuals infected from a single infected individual, is a measure of mosquito borne arbovirus transmission. Understanding the causes for the distribution of R₀ in any transmission cycle is a daunting challenge due to the lack of information on the genetic and environmental variances that influence R₀. Information about the major factors influencing R₀ for specific transmission cycles is essential to develop efficient and effective strategies to reduce transmission in different cycles and locations.

Reduced Risk of Importing Ebola Virus Disease because of Travel Restrictions in 2014: A Retrospective Epidemiological Modeling Study

Background

An epidemic of Ebola virus disease (EVD) from 2013–16 posed a serious risk of global spread during its early growth phase. A post-epidemic evaluation of the effectiveness of travel restrictions has yet to be conducted. The present study aimed to estimate the effectiveness of travel restrictions in reducing the risk of importation from mid-August to September, 2014, using a simple hazard-based statistical model.

Methodology/Principal Findings

The hazard rate was modeled as an inverse function of the effective distance, an excellent predictor of disease spread, which was calculated from the airline transportation network. By analyzing datasets of the date of EVD case importation from the 15^th of July to the 15^th of September 2014, and assuming that the network structure changed from the 8^th of August 2014 because of travel restrictions, parameters that characterized the hazard rate were estimated. The absolute risk reduction and relative risk reductions due to travel restrictions were estimated to be less than 1% and about 20%, respectively, for all models tested. Effectiveness estimates among African countries were greater than those for other countries outside Africa.

Conclusions

The travel restrictions were not effective enough to expect the prevention of global spread of Ebola virus disease. It is more efficient to control the spread of disease locally during an early phase of an epidemic than to attempt to control the epidemic at international borders. Capacity building for local containment and coordinated and expedited international cooperation are essential to reduce the risk of global transmission.

Assessing the global threat from Zika virus

First discovered in 1947, Zika virus (ZIKV) infection remained a little-known tropical disease until 2015, when its apparent association with a considerable increase in the incidence of microcephaly in Brazil raised alarms worldwide. There is limited information on the key factors that determine the extent of the global threat from ZIKV infection and resulting complications. Here, we review what is known about the epidemiology, natural history, and public health effects of ZIKV infection, the empirical basis for this knowledge, and the critical knowledge gaps that need to be filled.

Zika Fetal Neuropathogenesis: Etiology of a Viral Syndrome

The ongoing Zika virus epidemic in the Americas and the observed association with both fetal abnormalities (primary microcephaly) and adult autoimmune pathology (Guillain-Barré syndrome) has brought attention to this neglected pathogen. While initial case studies generated significant interest in the Zika virus outbreak, larger prospective epidemiology and basic virology studies examining the mechanisms of Zika viral infection and associated pathophysiology are only now starting to be published. In this review, we analyze Zika fetal neuropathogenesis from a comparative pathology perspective, using the historic metaphor of "TORCH" viral pathogenesis to provide context. By drawing parallels to other viral infections of the fetus, we identify common themes and mechanisms that may illuminate the observed pathology. The existing data on the susceptibility of various cells to both Zika and other flavivirus infections are summarized. Finally, we highlight relevant aspects of the known molecular mechanisms of flavivirus replication.

Predicting the international spread of Middle East respiratory syndrome (MERS)

Background

The Middle East respiratory syndrome (MERS) associated coronavirus has been imported via travelers into multiple countries around the world. In order to support risk assessment practice, the present study aimed to devise a novel statistical model to quantify the country-level risk of experiencing an importation of MERS case.

Methods

We analyzed the arrival time of each reported MERS importation around the world, i.e., the date on which imported cases entered a specific country, which was modeled as a dependent variable in our analysis. We also used openly accessible data including the airline transportation network to parameterize a hazard-based risk prediction model. The hazard was assumed to follow an inverse function of the effective distance (i.e., the minimum effective length of a path from origin to destination), which was calculated from the airline transportation data, from Saudi Arabia to each country. Both country-specific religion and the incidence data of MERS in Saudi Arabia were used to improve our model prediction.

Results

Our estimates of the risk of MERS importation appeared to be right skewed, which facilitated the visual identification of countries at highest risk of MERS importations in the right tail of the distribution. The simplest model that relied solely on the effective distance yielded the best predictive performance (Area under the curve (AUC) = 0.943) with 100 % sensitivity and 79.6 % specificity. Out of the 30 countries estimated to be at highest risk of MERS case importation, 17 countries (56.7 %) have already reported at least one importation of MERS. Although model fit measured by Akaike Information Criterion (AIC) was improved by including country-specific religion (i.e. Muslim majority country), the predictive performance as measured by AUC was not improved after accounting for this covariate.

Conclusions

Our relatively simple statistical model based on the effective distance derived from the airline transportation network data was found to help predicting the risk of importing MERS at the country level. The successful application of the effective distance model to predict MERS importations, particularly when computationally intensive large-scale transmission models may not be immediately applicable could have been benefited from the particularly low transmissibility of the MERS coronavirus.