Although the recent Zika virus (ZIKV) epidemic in the Americas and its link to birth defects have attracted a great deal of attention1,2, much remains unknown about ZIKV disease epidemiology and ZIKV evolution, in part owing to a lack of genomic data. Here we address this gap in knowledge by using multiple sequencing approaches to generate 110 ZIKV genomes from clinical and mosquito samples from 10 countries and territories, greatly expanding the observed viral genetic diversity from this outbreak. We analysed the timing and patterns of introductions into distinct geographic regions; our phylogenetic evidence suggests rapid expansion of the outbreak in Brazil and multiple introductions of outbreak strains into Puerto Rico, Honduras, Colombia, other Caribbean islands, and the continental United States. We find that ZIKV circulated undetected in multiple regions for many months before the first locally transmitted cases were confirmed, highlighting the importance of surveillance of viral infections. We identify mutations with possible functional implications for ZIKV biology and pathogenesis, as well as those that might be relevant to the effectiveness of diagnostic tests.

We use a data-driven global stochastic epidemic model to analyze the spread of the Zika virus (ZIKV) in the Americas. The model has high spatial and temporal resolution and integrates real-world demographic, human mobility, socioeconomic, temperature, and vector density data. We estimate that the first introduction of ZIKV to Brazil likely occurred between August 2013 and April 2014 (90% credible interval). We provide simulated epidemic profiles of incident ZIKV infections for several countries in the Americas through February 2017. The ZIKV epidemic is characterized by slow growth and high spatial and seasonal heterogeneity, attributable to the dynamics of the mosquito vector and to the characteristics and mobility of the human populations. We project the expected timing and number of pregnancies infected with ZIKV during the first trimester and provide estimates of microcephaly cases assuming different levels of risk as reported in empirical retrospective studies. Our approach represents a modeling effort aimed at understanding the potential magnitude and timing of the ZIKV epidemic and it can be potentially used as a template for the analysis of future mosquito-borne epidemics. Using a data-driven stochastic and spatial epidemic model, we present numerical results providing insight into the first introduction in the region and the epidemic dynamics across the Americas. We use the model to analyze the spatiotemporal spread and magnitude of the epidemic in the Americas through to February 2017, accounting for seasonal environmental factors and detailed population data. We also provide projections of the number of pregnancies infected with ZIKV during the first trimester, along with estimates for the number of microcephaly cases per country using three different levels of risk based on empirical retrospective studies (36, 37). ResultsIntroduction of ZIKV to the Americas. We identify 12 major transportation hubs in areas related to major events held in Brazil,

A systematic literature review was conducted to describe the epidemiology of dengue disease in Colombia. Searches of published literature in epidemiological studies of dengue disease encompassing the terms “dengue”, “epidemiology,” and “Colombia” were conducted. Studies in English or Spanish published between 1 January 2000 and 23 February 2012 were included. The searches identified 225 relevant citations, 30 of which fulfilled the inclusion criteria defined in the review protocol. The epidemiology of dengue disease in Colombia was characterized by a stable “baseline” annual number of dengue fever cases, with major outbreaks in 2001–2003 and 2010. The geographical spread of dengue disease cases showed a steady increase, with most of the country affected by the 2010 outbreak. The majority of dengue disease recorded during the review period was among those <15 years of age. Gaps identified in epidemiological knowledge regarding dengue disease in Colombia may provide several avenues for future research, namely studies of asymptomatic dengue virus infection, primary versus secondary infections, and under-reporting of the disease. Improved understanding of the factors that determine disease expression and enable improvement in disease control and management is also important.

Background Accurate seroprevalence estimates of SARS-CoV-2 in different populations could clarify the extent to which current testing strategies are identifying all active infection, and hence the true magnitude and spread of the infection. Our primary objective was to identify valid seroprevalence studies of SARS-CoV-2 infection and compare their estimates with the reported, and imputed, COVID-19 case rates within the same population at the same time point. Methods We searched PubMed, Embase, the Cochrane COVID-19 trials, and Europe-PMC for published studies and pre-prints that reported anti-SARS-CoV-2 IgG, IgM and/or IgA antibodies for serosurveys of the general community from 1 Jan to 12 Aug 2020. Results Of the 2199 studies identified, 170 were assessed for full text and 17 studies representing 15 regions and 118,297 subjects were includable. The seroprevalence proportions in 8 studies ranged between 1%-10%, with 5 studies under 1%, and 4 over 10%—from the notably hard-hit regions of Gangelt, Germany; Northwest Iran; Buenos Aires, Argentina; and Stockholm, Sweden. For seropositive cases who were not previously identified as COVID-19 cases, the majority had prior COVID-like symptoms. The estimated seroprevalences ranged from 0.56–717 times greater than the number of reported cumulative cases–half of the studies reported greater than 10 times more SARS-CoV-2 infections than the cumulative number of cases. Conclusions The findings show SARS-CoV-2 seroprevalence is well below “herd immunity” in all countries studied. The estimated number of infections, however, were much greater than the number of reported cases and deaths in almost all locations. The majority of seropositive people reported prior COVID-like symptoms, suggesting that undertesting of symptomatic people may be causing a substantial under-ascertainment of SARS-CoV-2 infections.