Zika virus genomes from Brazil: The Zika virus outbreak is a major cause for concern in Brazil, where it has been linked with increased reports of otherwise rare birth defects and neuropathology. In a phylogenetic analysis, Faria et al. infer a single introduction of Zika to the Americas and estimated the introduction date to be about May to December 2013—some 12 months earlier than the virus was reported. This timing correlates with major events in the Brazilian cultural calendar associated with increased traveler numbers from areas where Zika virus has been circulating. A correlation was also observed between incidences of microcephaly and week 17 of pregnancy. Science , this issue p. 345
Virus genomes reveal the establishment of Zika virus in Brazil and the Americas, and provide an appropriate timeframe for baseline (pre-Zika) microcephaly in different regions. Three papers in this issue present a wealth of new Zika virus (ZIKV) genome sequences and further insights into the genetic epidemiology of ZIKV. Nathan Grubaugh et al. provide 39 new ZIKV genome sequences from infected patients and Aedes aegypti mosquitoes in Florida. Phylogenetic analysis suggests that the virus has been introduced on multiple separate occasions, probably linked to travel from the Caribbean. They find a low probability of long-term persistence of ZIKV transmission chains within Florida, suggesting that the potential for future ZIKV outbreaks there will depend on transmission dynamics in the Americas. Nuno Faria et al. and Hayden Metsky et al. reconstruct the spread of ZIKV in Brazil and the Americas. Faria et al. provide 54 new ZIKV genomes, several sequenced in real time in a mobile genomics laboratory. They trace the spatial origins and spread of ZIKV in Brazil and the Americas and date the timing of the international spread of ZIKV from Brazil. They find that northeast Brazil had a crucial role in the establishment of the epidemic and the spread of the virus within Brazil and the Americas. Metsky et al. generate 110 ZIKV genomes from clinical and mosquito samples from ten regions. They also see rapid expansion of the epidemic within Brazil and multiple introductions to other geographic areas. In agreement with Faria et al., they find that ZIKV circulated unobserved for many months before transmission was detected. Metsky et al. additionally describe ZIKV evolution and discuss how the accumulation of mutations might affect the performance of diagnostic tests in the future. 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.
Arbovirus risk in Brazil: Despite the existence of an effective vaccine for yellow fever, there are still almost 80,000 fatalities from this infection each year. Since 2016, there has been a resurgence of cases in Africa and South America—and this at a time when the vaccine is in short supply. The worry is that yellow fever will spread from the forests to the cities, because its vector, Aedes spp. mosquitoes, are globally ubiquitous. Faria et al. integrate genomic, epidemiological, and case distribution data from Brazil to estimate patterns of geographic spread, the risks of virus exposure, and the contributions of rural versus urban transmission (see the Perspective by Barrett). Currently, the yellow fever epidemic in Brazil seems to be driven by infections acquired while visiting forested areas and indicates spillover from susceptible wild primates. Science , this issue p. 894 ; see also p. 847
Cases of a novel coronavirus were first reported in Wuhan, Hubei province, China, in December 2019 and have since spread across the world. Epidemiological studies have indicated human-to-human transmission in China and elsewhere. To aid the analysis and tracking of the COVID-19 epidemic we collected and curated individual-level data from national, provincial, and municipal health reports, as well as additional information from online reports. All data are geo-coded and, where available, include symptoms, key dates (date of onset, admission, and confirmation), and travel history. The generation of detailed, real-time, and robust data for emerging disease outbreaks is important and can help to generate robust evidence that will support and inform public health decision making.
Since late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock. We jointly analysed datasets describing the epidemic of yellow fever, vector suitability, human demography, and mobility in central Africa to understand and predict the spread of yellow fever virus. We used a standard logistic model to infer the district-specific yellow fever virus infection risk during the course of the epidemic in the region. The early spread of yellow fever virus was characterised by fast exponential growth (doubling time of 5-7 days) and fast spatial expansion (49 districts reported cases after only 3 months) from Luanda, the capital of Angola. Early invasion was positively correlated with high population density (Pearson's r 0·52, 95% CI 0·34-0·66). The further away locations were from Luanda, the later the date of invasion (Pearson's r 0·60, 95% CI 0·52-0·66). In a Cox model, we noted that districts with higher population densities also had higher risks of sustained transmission (the hazard ratio for cases ceasing was 0·74, 95% CI 0·13-0·92 per log-unit increase in the population size of a district). A model that captured human mobility and vector suitability successfully discriminated districts with high risk of invasion from others with a lower risk (area under the curve 0·94, 95% CI 0·92-0·97). If at the start of the epidemic, sufficient vaccines had been available to target 50 out of 313 districts in the area, our model would have correctly identified 27 (84%) of the 32 districts that were eventually affected. Our findings show the contributions of ecological and demographic factors to the ongoing spread of the yellow fever outbreak and provide estimates of the areas that could be prioritised for vaccination, although other constraints such as vaccine supply and delivery need to be accounted for before such insights can be translated into policy. Wellcome Trust.