Programa de Computação Científica, Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, Brazil.
Politécnico Grancolombiano, Escuela de Optimización, Diseño y Automatización, Bogotá, Colombia.
Malar J. 2023 Feb 10;22(1):49. doi: 10.1186/s12936-023-04464-y.
As controlling malaria transmission remains a public-health challenge in the Brazilian Amazon basin, the National Surveillance System for Malaria (SIVEP-MALARIA) has registered malaria notifications for over fifteen years helping in the decision-making on control and elimination. As a surveillance database, the system is prone to reporting delays, and knowledge about reporting patterns is essential in decisions.
This study contains an analysis of temporal and state trends of reporting times in a total of 1,580,617 individual malaria reports from January 2010 to December 2020, applying procedures for statistical distribution fitting. A nowcasting technique was applied to show an estimation of number of cases using a statistical model of reporting delays.
Reporting delays increased over time for the states of Amazonas, Rondônia, Roraima, and Pará. Amapá has maintained a similar reporting delay pattern, while Acre decreased reporting delay between 2010 and 2020. Predictions were more accurate in states with lower reporting delays. The temporal evolution of reporting delays only showed a decrease in malaria reports in Acre from 2010 to 2020.
Malaria notifications may take days or weeks to enter the national surveillance database. The reporting times are likely to impact incidence estimation over periods when data is incomplete, whilst the impact of delays becomes smaller for retrospective analysis. Short-term assessments for the estimation of malaria incidence from the malaria control programme must deal with reporting delays.
在巴西亚马孙流域，控制疟疾传播仍然是公共卫生面临的挑战，国家疟疾监测系统（SIVEP-MALARIA）已经登记了超过十五年的疟疾报告，这有助于控制和消除疟疾的决策。作为一个监测数据库，该系统容易出现报告延迟，了解报告模式对于决策至关重要。
本研究分析了 2010 年 1 月至 2020 年 12 月期间总共 1580617 例个体疟疾报告的时间和州趋势，应用了统计分布拟合程序。应用即时预测技术，使用报告延迟的统计模型来估计病例数。
亚马逊州、朗多尼亚州、罗赖马州和帕拉州的报告延迟随时间增加。阿马帕州一直保持着类似的报告延迟模式，而阿克雷州在 2010 年至 2020 年间减少了报告延迟。预测在报告延迟较低的州更准确。报告延迟的时间演变仅显示 2010 年至 2020 年阿克雷州的疟疾报告有所减少。
疟疾通知可能需要几天或几周的时间才能进入国家监测数据库。在数据不完整的时期，报告时间可能会影响发病率估计，而对于回顾性分析，延迟的影响会变小。从疟疾控制计划中估计疟疾发病率的短期评估必须处理报告延迟问题。
