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

Zika beyond the Americas: Travelers as sentinels of Zika virus transmission. A GeoSentinel analysis, 2012 to 2016.

Background: Zika virus (ZIKV) was first isolated in Africa; decades later, caused large outbreaks in the Pacific, and is considered endemic in Asia. We aim to describe ZIKV disease epidemiology outside the Americas, the importance of travelers as sentinels of disease transmission, and discrepancies in travel advisories from major international health organizations. Methods and findings This descriptive analysis using GeoSentinel Surveillance Network records involves sixty-four travel and tropical medicine clinics in 29 countries. Ill returned travelers with a confirmed or probable diagnosis of ZIKV disease acquired in Africa, Asia and the Pacific seen between 1 January 2012 and 31 December 2016 are included, and the frequencies of demographic, trip, and diagnostic characteristics described. ZIKV was acquired in Asia (18), the Pacific (10) and Africa (1). For five countries (Indonesia, Philippines, Thailand, Vietnam, Cameroon), GeoSentinel patients were sentinel markers of recent Zika activity. Additionally, the first confirmed ZIKV infection acquired in Kiribati was reported to GeoSentinel (2015), and a probable case was reported from Timor Leste (April 2016), representing the only case known to date. Review of Zika situation updates from major international health authorities for country risk classifications shows heterogeneity in ZIKV country travel advisories. Conclusions: Travelers are integral to the global spread of ZIKV, serving as sentinel markers of disease activity. Although GeoSentinel data are collected by specialized clinics and do not capture all imported cases, we show that surveillance of imported infections by returned travelers augments local surveillance system data regarding ZIKV epidemiology and can assist with risk categorization by international authorities. However, travel advisories are variable due to risk uncertainties

Establishment and cryptic transmission of Zika virus in Brazil and the Americas

Transmission of Zika virus (ZIKV) in the Americas was first confirmed in May 2015 in northeast Brazil1. Brazil has had the highest number of reported ZIKV cases worldwide (more than 200,000 by 24 December 20162) and the most cases associated with microcephaly and other birth defects (2,366 confirmed by 31 December 20162). Since the initial detection of ZIKV in Brazil, more than 45 countries in the Americas have reported local ZIKV transmission, with 24 of these reporting severe ZIKV-associated disease3. However, the origin and epidemic history of ZIKV in Brazil and the Americas remain poorly understood, despite the value of this information for interpreting observed trends in reported microcephaly. Here we address this issue by generating 54 complete or partial ZIKV genomes, mostly from Brazil, and reporting data generated by a mobile genomics laboratory that travelled across northeast Brazil in 2016. One sequence represents the earliest confirmed ZIKV infection in Brazil. Analyses of viral genomes with ecological and epidemiological data yield an estimate that ZIKV was present in northeast Brazil by February 2014 and is likely to have disseminated from there, nationally and internationally, before the first detection of ZIKV in the Americas. Estimated dates for the international spread of ZIKV from Brazil indicate the duration of pre-detection cryptic transmission in recipient regions. The role of northeast Brazil in the establishment of ZIKV in the Americas is further supported by geographic analysis of ZIKV transmission potential and by estimates of the basic reproduction number of the virus

Climate Change and the Transmission of Vector-Borne Diseases: A Review

This article reviews studies examining the relationship between climate variability and the transmission of vector- and rodent-borne diseases, including malaria, dengue fever, Ross River virus infection, and hemorrhagic fever with renal syndrome. The review has evaluated their study designs, statistical analysis methods, usage of meteorological variables, and results of those studies. The authors found that the limitations of analytical methods exist in most of the articles. Besides climatic variables, few of them have included other factors that can affect the transmission of vector-borne disease (eg, socioeconomic status). In addition, the quantitative relationship between climate and vector-borne diseases is inconsistent. Further research should be conducted among different populations with various climatic/ecological regions by using appropriate statistical models