Evidence map›Paper›PMID 34886507›Full record

ArticleInternational journal of environmental research and public health2021

Epidemiological Trends of Malaria in Five Years and under Children of Nsanje District in Malawi, 2015-2019.

Theodore Gondwe, Yongi Yang, Simeon Yosefe, Maisa Kasanga, Griffin Mulula, Mphatso Prince Luwemba, Annie Jere, Victor Daka, Tobela Mudenda

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Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

9 authors.

Theodore GondweDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China.ORCID 0000-0002-3120-6066
Yongi YangDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
Simeon YosefeDepartment of Planning and Policy Development, Ministry of Health Malawi, Lilongwe 30377, Malawi.
Maisa KasangaDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China.ORCID 0000-0003-1724-7934
Griffin MululaDepartment of Education Planning, Ministry of Education Malawi, Lilongwe 328, Malawi.
Mphatso Prince LuwembaMathematical Department, Chancellor College, University of Malawi, Zomba 280, Malawi.
Annie JereSchool of Engineering, Malawi University of Business and Applied Sciences, Blantyre 303, Malawi.
Victor DakaPublic Health Department, Michael Chilufya Sata School of Medicine, Copperbelt University, Ndola 21692, Zambia.
Tobela MudendaPathology Department, Ndola Teaching Hospital, Ndola 10101, Zambia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMalaria continues to be a major public health problem in Malawi and the greatest load of mortality and morbidity occurs in children five years and under. However, there is no information yet regarding trends and predictions of malaria incidence in children five years and under at district hospital level, particularly at Nsanje district hospital.

aimTherefore, this study aimed at investigating the trends of malaria morbidity and mortality in order to design appropriate interventions on the best approach to contain the disease in the near future. METHODOLOGY: Trend analysis of malaria morbidity and mortality together with time series analysis using the SARIMA (Seasonal Autoregressive Integrated Moving Average) model was used to predict malaria incidence in Nsanje district.

resultsThe SARIMA model used malaria cases from 2015 to 2019 and created the best model to forecast the malaria cases in Nsanje from 2020 to 2022. An SARIMA (0, 1, 2) (0,1,1)

conclusionThe mortality and morbidity trend showed that malaria cases were growing at a fluctuating rate at Nsanje district hospital. The relative errors between the actual values and predicted values indicated that the predicted values matched the actual values well. Therefore, the model proved that it was adequate to forecast monthly malaria cases and it had a good fit, hence, was appropriate for this study.

Indexed as

MalariaModels, StatisticalChildForecastingHumansIncidenceMalawiSeasonsmalaria incidenceSARIMAtime series

Identifiers

PMID34886507
PMCPMC8657219

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.