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.

BackgroundInfectious diseases are a leading threat to public health. Accurate and timely monitoring of disease risk and progress can reduce their impact. Mentioning a disease in social networks is correlated with physician visits by patients, and can be used to estimate disease activity. Dengue is the fastest growing mosquito-borne viral disease, with an estimated annual incidence of 390 million infections, of which 96 million manifest clinically. Dengue burden is likely to increase in the future owing to trends toward increased urbanization, scarce water supplies and, possibly, environmental change. The epidemiological dynamic of Dengue is complex and difficult to predict, partly due to costly and slow surveillance systems.Methodology / Principal findingsIn this study, we aimed to quantitatively assess the usefulness of data acquired by Twitter for the early detection and monitoring of Dengue epidemics, both at country and city level at a weekly basis. Here, we evaluated and demonstrated the potential of tweets modeling for Dengue estimation and forecast, in comparison with other available web-based data, Google Trends and Wikipedia access logs. Also, we studied the factors that might influence the goodness-of-fit of the model. We built a simple model based on tweets that was able to ‘nowcast’, i.e. estimate disease numbers in the same week, but also ‘forecast’ disease in future weeks. At the country level, tweets are strongly associated with Dengue cases, and can estimate present and future Dengue cases until 8 weeks in advance. At city level, tweets are also useful for estimating Dengue activity. Our model can be applied successfully to small and less developed cities, suggesting a robust construction, even though it may be influenced by the incidence of the disease, the activity of Twitter locally, and social factors, including human development index and internet access.ConclusionsTweets association with Dengue cases is valuable to assist traditional Dengue surveillance at real-time and low-cost. Tweets are able to successfully nowcast, i.e. estimate Dengue in the present week, but also forecast, i.e. predict Dengue at until 8 weeks in the future, both at country and city level with high estimation capacity.

Previous phylogenetic analyses indicated that the ZIKV epidemic was caused by the introduction of a single Asian genotype lineage into the Americas around late 2013, at least one year before its detection there 4 . An estimated 100 million people in the Americas are predicted to be at risk of acquiring ZIKV once the epidemic has reached its full extent 5 . However, little is known about the genetic diversity and transmission history of the virus in different regions in Brazil 6 . Reconstructing ZIKV spread from case reports alone is challenging because symptoms (typically fever, headache, joint pain, rashes, and conjunctivitis) overlap with those caused by co-circulating arthropod-borne viruses 7 and due to a lack of nationwide ZIKV-specific surveillance in Brazil before 2016. [Figure 1 around here]To address this we undertook a collaborative investigation of ZIKV molecular epidemiology in Brazil, including results from a mobile genomics laboratory that travelled through NE Brazil during June 2016 (the ZiBRA project; http://www.zibraproject.org). Of five regions of Brazil (Fig. 1a), the Northeast region (NE Brazil) has the most notified ZIKV cases (40% of Brazilian cases) and the most confirmed microcephaly cases (76% of Brazilian cases, to 31 Dec 2016 2 ), raising questions about why the region has been so severely affected 8 . Further, NE Brazil is the most populous region of Brazil with the potential for year-round ZIKV transmission 9 . With the support of the Brazilian Ministry of Health and other institutions (Acknowledgements), the ZiBRA lab screened 1330 samples (almost exclusively serum or blood) from patients residing in 82 municipalities across five federal states in NE Brazil ( Fig. 1 On average, ZIKV viremia persists for 10 days after infection; symptoms develop ~6 days after infection and can last 1-2 weeks 10 . In line with previous observations in Colombia 11 , we found that the RT-qPCR+ samples in NE Brazil were, on average, collected only two days after onset of symptoms. The median RT-qPCR cycle threshold (Ct) value of positive samples was correspondingly high, at 36 (Extended Data Fig. 1). For NE Brazil, the time series of RT-qPCR+ cases was positively correlated with the number of weekly-notified cases (Pearson's ρ=0.62; Fig. 1b).The ability of the mosquito vector Aedes aegypti to transmit ZIKV is determined by ecological factors that affect adult survival, viral replication, and infective periods 12 .To investigate the receptivity of each Brazilian region to ZIKV transmission, we used a measure of vector climatic suitability derived from monthly temperature, relative humidity, and precipitation data 9 . Using linear regression we find that, for each Brazilian region, there is a strong association between estimated climatic suitability and weekly notified cases (Figs. 1b,1c; adjusted R 2 >0.84, P<0.001; Extended Data Table 2). Similar to previous findings obtained for dengue virus outbreaks 13,14 , notified ZIKV cases lag climatic suitability by ~4 to 6 weeks in all regions, except NE Brazil,...