Evidence map›Paper›PMID 36765345›Full record

ArticleMalaria journal2023

Notification of malaria cases in the Brazilian Amazon Basin from 2010 to 2020: an analysis of the reporting times.

Mario J C Ayala, Naiara C M Valiati, Leonardo S Bastos, Daniel A M Villela

Abstract read
In one paragraph

Article in Malaria journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mario J C AyalaPrograma de Computação Científica, Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, Brazil.
Naiara C M ValiatiPrograma de Computação Científica, Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, Brazil.
Leonardo S BastosPrograma de Computação Científica, Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, Brazil.
Daniel A M VillelaPrograma de Computação Científica, Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, Brazil. daniel.villela@fiocruz.br.

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 309569/2019-2Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Finance Code 001
6 · The paper itself

Abstract

backgroundAs 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.

methodsThis 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.

resultsReporting 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.

conclusionMalaria 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.

Indexed as

MalariaPopulation SurveillanceBrazilHumansIncidenceRetrospective StudiesHealth surveillanceMalariaReporting times

Identifiers

PMID36765345
PMCPMC9913006

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