RESUMEN
OBJECTIVES: Quantify the risk of mental health (MH)-related emergency department visits (EDVs) due to heat, in the city of Curitiba, Brazil. DESIGN: Daily time series analysis, using quasi-Poisson combined with distributed lag non-linear model on EDV for MH disorders, from 2017 to 2021. SETTING: All nine emergency centres from the public health system, in Curitiba. PARTICIPANTS: 101 452 EDVs for MH disorders and suicide attempts over 5 years, from patients residing inside the territory of Curitiba. MAIN OUTCOME MEASURE: Relative risk of EDV (RREDV) due to extreme mean temperature (24.5°C, 99th percentile) relative to the median (18.02°C), controlling for long-term trends, air pollution and humidity, and measuring effects delayed up to 10 days. RESULTS: Extreme heat was associated with higher single-lag EDV risk of RREDV 1.03(95% CI 1.01 to 1.05-single-lag 2), and cumulatively of RREDV 1.15 (95% CI 1.05 to 1.26-lag-cumulative 0-6). Strong risk was observed for patients with suicide attempts (RREDV 1.85, 95% CI 1.08 to 3.16) and neurotic disorders (RREDV 1.18, 95% CI 1.06 to 1.31). As to demographic subgroups, females (RREDV 1.20, 95% CI 1.08 to 1.34) and patients aged 18-64 (RREDV 1.18, 95% CI 1.07 to 1.30) were significantly endangered. Extreme heat resulted in lower risks of EDV for patients with organic disorders (RREDV 0.60, 95% CI 0.40 to 0.89), personality disorders (RREDV 0.48, 95% CI 0.26 to 0.91) and MH in general in the elderly ≥65 (RREDV 0.77, 95% CI 0.60 to 0.98). We found no significant RREDV among males and patients aged 0-17. CONCLUSION: The risk of MH-related EDV due to heat is elevated for the entire study population, but very differentiated by subgroups. This opens avenue for adaptation policies in healthcare: such as monitoring populations at risk and establishing an early warning systems to prevent exacerbation of MH episodes and to reduce suicide attempts. Further studies are welcome, why the reported risk differences occur and what, if any, role healthcare seeking barriers might play.
Asunto(s)
Calor , Salud Mental , Masculino , Anciano , Femenino , Humanos , Brasil/epidemiología , Factores de Tiempo , Servicio de Urgencia en HospitalRESUMEN
BACKGROUND: Dengue outbreaks are increasing in frequency over space and time, affecting people's health and burdening resource-constrained health systems. The ability to detect early emerging outbreaks is key to mounting an effective response. The early warning and response system (EWARS) is a toolkit that provides countries with early-warning systems for efficient and cost-effective local responses. EWARS uses outbreak and alarm indicators to derive prediction models that can be used prospectively to predict a forthcoming dengue outbreak at district level. METHODS: We report on the development of the EWARS tool, based on users' recommendations into a convenient, user-friendly and reliable software aided by a user's workbook and its field testing in 30 health districts in Brazil, Malaysia and Mexico. FINDINGS: 34 Health officers from the 30 study districts who had used the original EWARS for 7 to 10 months responded to a questionnaire with mainly open-ended questions. Qualitative content analysis showed that participants were generally satisfied with the tool but preferred open-access vs. commercial software. EWARS users also stated that the geographical unit should be the district, while access to meteorological information should be improved. These recommendations were incorporated into the second-generation EWARS-R, using the free R software, combined with recent surveillance data and resulted in higher sensitivities and positive predictive values of alarm signals compared to the first-generation EWARS. Currently the use of satellite data for meteorological information is being tested and a dashboard is being developed to increase user-friendliness of the tool. The inclusion of other Aedes borne viral diseases is under discussion. CONCLUSION: EWARS is a pragmatic and useful tool for detecting imminent dengue outbreaks to trigger early response activities.