Evidence map›Paper›PMID 35164781›Full record

ArticleMalaria journal2022

The impact of Covid-19 on malaria services in three high endemic districts in Rwanda: a mixed-method study.

Dieudonne Hakizimana, Christian Ntizimira, Aimable Mbituyumuremyi, Emmanuel Hakizimana, Hani Mahmoud, Pascal Birindabagabo, Clarisse Musanabaganwa, Diane Gashumba

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
9.2field-weighted citation impact, top 1% of its field
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

30 citing papers in PubMed, 47 citations in OpenAlex.

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  13. Mathematical assessment of the role of intervention programs for malaria control.medRxiv : the preprint server for health sciences · 2023
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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

8 authors at 2 institutions in 1 country.

Dieudonne HakizimanaUniversity of Global Health Equity (UGHE), Kigali, Rwanda. dieudonnehakiziman@gmail.com.ORCID http://orcid.org/0000-0002-5379-4129
Christian NtizimiraHealth Concepts and Innovation Solutions (HCIS), Kigali, Rwanda.
Aimable MbituyumuremyiRwanda Biomedical Center (RBC), Kigali, Rwanda.
Emmanuel HakizimanaRwanda Biomedical Center (RBC), Kigali, Rwanda.
Hani MahmoudResolve To Save Lives, New York, NY, USA.
Pascal BirindabagaboHealth Concepts and Innovation Solutions (HCIS), Kigali, Rwanda.
Clarisse MusanabaganwaRwanda Biomedical Center (RBC), Kigali, Rwanda.
Diane GashumbaHealth Concepts and Innovation Solutions (HCIS), Kigali, Rwanda.
Rwanda Biomedical Center · RWUniversity of Global Health Equity · RW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRwanda has achieved impressive reductions in malaria morbidity and mortality over the past two decades. However, the disruption of essential services due to the current Covid-19 pandemic can lead to a reversal of these gains in malaria control unless targeted, evidence-based interventions are implemented to mitigate the impact of the pandemic. The extent to which malaria services have been disrupted has not been fully characterized. This study was conducted to assess the impact of Covid-19 on malaria services in Rwanda.

methodsA mixed-methods study was conducted in three purposively selected districts in Rwanda. The quantitative data included malaria aggregated data reported at the health facility level and the community level. The data included the number of malaria tests, uncomplicated malaria cases, severe malaria cases, and malaria deaths. The qualitative data were collected using focus group discussions with community members and community health workers, as well as in-depth interviews with health care providers and staff working in the malaria programme. Interrupted time series analysis was conducted to compare changes in malaria presentations between the pre-Covid-19 period (January 2019 to February 2020) and Covid-19 period (from March 2020 to November 2020). The constant comparative method was used in qualitative thematic analysis.

resultsCompared to the pre-Covid-19 period, there was a monthly reduction in patients tested in health facilities of 4.32 per 1000 population and a monthly increase in patients tested in the community of 2.38 per 1000 population during the Covid-19 period. There was no change in the overall presentation rate for uncomplicated malaria. The was a monthly reduction in the proportion of severe malaria of 5.47 per 100,000 malaria cases. Additionally, although healthcare providers continued to provide malaria services, they were fearful that this would expose them and their families to Covid-19. Covid-19 mitigation measures limited the availability of transportation options for the community to seek care in health facilities and delayed the implementation of some key malaria interventions. The focus on Covid-19-related communication also reduced the amount of health information for other diseases provided to community members.

conclusionThe Covid-19 pandemic resulted in patients increasingly seeking care in the community and poses challenges to maintaining delivery of malaria services in Rwanda. Interventions to mitigate these challenges should focus on strengthening programming for the community and home-based care models and integrating malaria messages into Covid-19-related communication. Additionally, implementation of the interrupted interventions should be timed and overlap with the malaria transmission season to mitigate Covid-19 consequences on malaria.

Indexed as

COVID-19MalariaCommunity Health WorkersHumansPandemicsRwandaSARS-CoV-2Covid-19MalariaMixed-methodsRwandaService delivery

Identifiers

PMID35164781
PMCPMC8845295
OpenAlexW4226027356

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.