Prediction of Zika-confirmed cases in Brazil and Colombia using Google Trends.

Zika virus infection in humans has been linked to severe neurological sequels and foetal malformations. The rapidly evolving epidemics and serious complications made the frequent updates of Zika virus mandatory. Web search query has emerged as a low-cost real-time surveillance system to anticipate infectious diseases' outbreaks. Hence, we developed a prediction model that could predict Zika-confirmed cases based on Zika search volume in Google Trends. We extracted weekly confirmed Zika cases of two epidemic countries, Brazil and Colombia. We got the weekly Zika search volume in the two countries from Google Trends. We used standard time-series regression (TSR) to predict the weekly confirmed Zika cases based on the Zika search volume (Zika query). The basis TSR model - using 1-week lag of Zika query and using 1-week lag of Zika cases as a control for autocorrelation - was the best for predicting Zika cases in Brazil and Colombia because it balanced the performance of the model and the advance time in the prediction. Our results showed that we could use Google search queries to predict Zika cases 1 week earlier before the outbreak. These findings are important to help healthcare authorities evaluate the outbreak and take necessary precautions.

Association between maternal depression and risk of infant diarrhea: a systematic review and meta-analysis.

OBJECTIVE: To systematically review the evidence for an association between maternal depression and the risk of diarrheal illness in infants. STUDY DESIGN: This study is a meta-analysis. METHODS: Nine databases were searched systematically for studies that investigated the risk of diarrheal illness in infants born to mothers with depression. RESULTS: Our search strategy yielded 10 studies of the association between maternal depression and the risk of diarrheal illness in infants: eight studies of postnatal depression, two studies of antenatal depression, and one study of perinatal depression. Our meta-analysis showed that infants born to mothers with postnatal depression were more likely to develop diarrheal illness (odds ratio [OR] = 1.902, 95% confidence interval [95% CI] = 1.385-2.612, P < 0.001, n = 18,585). A similar trend was noted for antenatal depression (OR = 2.703, 95% CI = 0.920-7.942, P = 0.071, n = 583). Only one study reported an association between perinatal depression and risk of diarrhea in infants (OR = 1.848, log OR = 0.614, standard error = 0.093, n = 107,587). CONCLUSIONS: Only a few studies so far have identified an association between maternal depression and risk of diarrhea in infants. The evidence available to date suggests that infants born to mothers with depression are more likely to develop diarrhea than infants whose mothers do not have depression.