Early detection of respiratory disease outbreaks through primary healthcare data.

Background: The emergence of coronavirus disease 2019 (COVID-19) in 2020 highlighted the relevance of surveillance systems in detecting early signs of potential outbreaks, thus enabling public health authorities to act before the pathogen becomes widespread. Syndromic digital surveillance through web applications has played a crucial role in monitoring the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. However, this approach requires expensive infrastructure, which is not available in developing countries. Pre-existing sources of information, such as encounters in primary health care (PHC), can provide valuable data for a syndromic surveillance system. Here we evaluated the utility of PHC data to identify early warning signals of the first COVID-19 outbreak in Bahia-Brazil in 2020. Methods: We compared the weekly counts of PHC encounters due to respiratory complaints and the number of COVID-19 cases in 2020 in Bahia State - Brazil. We used the data from December 2016 to December 2019 to predict the expected number of encounters in 2020. We analysed data aggregated by geographic regions (n = 34) and included those where historical PHC data was available for at least 70% of the population. Results: Twenty-one out of 34 regions met the inclusion criteria. We observed that notification of COVID-19 cases was preceded by at least two weeks with an excess of encounters of respiratory complaints in 18/21 (86%) of the regions analysed and four weeks or more in 10/21 (48%) regions. Conclusions: Digital syndromic surveillance systems based on already established PHC databases may add time to preparedness and response to emerging epidemics.

Safety of BNT162b2 and CoronaVac during pregnancy on birth outcomes and neonatal mortality: a cohort study from Brazil.

BACKGROUND: COVID-19 vaccines have been shown to protect pregnant individuals against mild and severe COVID-19 outcomes. However, limited safety data are available for inactivated (CoronaVac) and mRNA (BNT162b2) vaccines during pregnancy regarding their effect on birth outcomes and neonatal mortality, especially in low- and middle-income countries. METHODS: We conducted a retrospective population-based cohort study in Rio de Janeiro, Brazil, with 17 513 singleton live births conceived between 15 May 2021 and 23 October 2021. The primary exposure was maternal vaccination with CoronaVac or mRNA BNT162b2 vaccines and sub-analyses were performed by the gestational trimester of the first dose and the number of doses given during pregnancy. The outcomes were pre-term birth (PTB), small for gestational age (SGA), low birthweight (LBW), low Apgar 5 and neonatal death. We used the Cox model to estimate the hazard ratio (HR) with a 95% CI and applied the inverse probability of treatment weights to generate adjusted HRs. RESULTS: We found no significant increase in the risk of PTB (HR: 0.98; 95% CI 0.88, 1.10), SGA (HR: 1.09; 95% CI 0.96, 1.27), LBW (HR: 1.00; 95% CI 0.88, 1.14), low Apgar 5 (HR: 0.81; 95% CI 0.55, 1.22) or neonatal death (HR: 0.88; 95% CI 0.56, 1.48) in women vaccinated with CoronaVac or BNT162b2 vaccines. These findings were consistent across sub-analyses stratified by the gestational trimester of the first dose and the number of doses given during pregnancy. We found mild yet consistent protection against PTB in women who received different vaccine platforms during the third trimester of pregnancy (any vaccines, HR: 0.78; 95% CI 0.63, 0.98; BNT162b2, HR: 0.75; 95% CI 0.59, 0.99). CONCLUSIONS: This study provides evidence that COVID-19 vaccination in all trimesters of pregnancy, irrespective of the vaccine type, is safe and does not increase the risk of adverse birth outcomes or neonatal deaths.