Delay in death reporting affects timely monitoring and modeling of the COVID-19 pandemic

Autor: Carolina Abreu de Carvalho, Vitória Abreu de Carvalho, Marcos Adriano Garcia Campos, Bruno Luciano Carneiro Alves de Oliveira, Eduardo Moraes Diniz, Alcione Miranda dos Santos, Bruno Feres de Souza, Antônio Augusto Moura da Silva
Jazyk: English<br />Spanish; Castilian<br />Portuguese
Rok vydání: 2021
Předmět:
Zdroj: Cadernos de Saúde Pública, Vol 37, Iss 7 (2021)
Druh dokumentu: article
ISSN: 1678-4464
0102-311x
DOI: 10.1590/0102-311x00292320
Popis: This study describes the COVID-19 death reporting delay in the city of São Luís, Maranhão State, Brazil, and shows its impact on timely monitoring and modeling of the COVID-19 pandemic, while seeking to ascertain how nowcasting can improve death reporting delay. We analyzed COVID-19 death data reported daily in the Epidemiological Bulletin of the State Health Secretariat of Maranhão and calculated the reporting delay from March 23 to August 29, 2020. A semi-mechanistic Bayesian hierarchical model was fitted to illustrate the impact of death reporting delay and test the effectiveness of a Bayesian Nowcasting in improving data quality. Only 17.8% of deaths were reported without delay or the day after, while 40.5% were reported more than 30 days late. Following an initial underestimation due to reporting delay, 644 deaths were reported from June 7 to August 29, although only 116 deaths occurred during this period. Using the Bayesian nowcasting technique partially improved the quality of mortality data during the peak of the pandemic, providing estimates that better matched the observed scenario in the city, becoming unusable nearly two months after the peak. As delay in death reporting can directly interfere with assertive and timely decision-making regarding the COVID-19 pandemic, the Brazilian epidemiological surveillance system must be urgently revised and notifying the date of death must be mandatory. Nowcasting has proven somewhat effective in improving the quality of mortality data, but only at the peak of the pandemic.
Databáze: Directory of Open Access Journals
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