Evidence map›Paper›PMID 38754899›Full record

ArticleBMJ global health2024

Enhancing SARS-CoV-2 surveillance in Malawi using telephone syndromic surveillance from July 2020 to April 2022.

Godfrey Woelk, Thulani Maphosa, Rhoderick Machekano, Annie Chauma-Mwale, Lucky Makonokaya, Suzgo B Zimba, Rachel Kanyenda Chamanga, Rose Nyirenda, Andrew Auld, Evelyn Kim and 5 more

Abstract read
In one paragraph

Article in BMJ global health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

15 authors.

Godfrey Woelk *Elizabeth Glaser Pediatric AIDS Foundation, Washington, District of Columbia, USA.
Thulani Maphosa *Elizabeth Glaser Pediatric AIDS Foundation, Lilongwe, Malawi tmaphosa@pedaids.org.ORCID http://orcid.org/0000-0001-5164-8913
Rhoderick Machekano *Elizabeth Glaser Pediatric AIDS Foundation, Washington, District of Columbia, USA.
Annie Chauma-MwalePublic Health Institute of Malawi, Ministry of Health, Lilongwe, Malawi.
Lucky MakonokayaElizabeth Glaser Pediatric AIDS Foundation, Lilongwe, Malawi.
Suzgo B ZimbaElizabeth Glaser Pediatric AIDS Foundation, Lilongwe, Malawi.
Rachel Kanyenda ChamangaElizabeth Glaser Pediatric AIDS Foundation, Lilongwe, Malawi.
Rose NyirendaMinistry of Health Department of HIV and AIDS, Lilongwe, Central Region, Malawi.
Andrew AuldUS Centers for Disease Control and Prevention, Division of Global HIV and TB, Lilongwe, Malawi.
Evelyn KimUS Centers for Disease Control and Prevention, Division of Global HIV and TB, Lilongwe, Malawi.
Veena SampathkumarElizabeth Glaser Pediatric AIDS Foundation, Lilongwe, Malawi.
Allan AhimbisibweElizabeth Glaser Pediatric AIDS Foundation, Lilongwe, Malawi.
Louiser Kalitera *Elizabeth Glaser Pediatric AIDS Foundation, Lilongwe, Malawi.
Lindsay KimUS Centers for Disease Control and Prevention, Division of Global HIV and TB, Lilongwe, Malawi.
Alice MaidaUS Centers for Disease Control and Prevention, Division of Global HIV and TB, Lilongwe, Malawi.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMonitoring the SARS-CoV-2 pandemic in low-resource countries such as Malawi requires cost-effective surveillance strategies. This study explored the potential utility of phone-based syndromic surveillance in terms of its reach, monitoring trends in reported SARS-CoV-2-like/influenza-like symptoms (CLS/ILS), SARS-CoV-2 testing and mortality.

methodsMobile phone-based interviews were conducted between 1 July 2020 and 30 April 2022, using a structured questionnaire. Randomly digital dialled numbers were used to reach individuals aged ≥18 years who spoke Chichewa or English. Verbal consent was obtained, and trained research assistants with clinical and nursing backgrounds collected information on age, sex, region of residence, reported CLS/ILS in the preceding 2 weeks, SARS-CoV-2 testing and history of household illness and death. Data were captured on tablets using the Open Data Kit database. We performed a descriptive analysis and presented the frequencies and proportions with graphical representations over time.

findingsAmong 356 525 active phone numbers, 138 751 (38.9%) answered calls, of which 104 360 (75.2%) were eligible, 101 617 (97.4%) consented to participate, and 100 160 (98.6%) completed the interview. Most survey respondents were aged 25-54 years (72.7%) and male (65.1%). The regional distribution of the respondents mirrored the regional population distribution, with 45% (44%) in the southern region, 41% (43%) in the central region and 14% (13%) in the northern region. The reported SARS-CoV2 positivity rate was 11.5% (107/934). Of the 7298 patients who reported CLS/ILS, 934 (12.8%) reported having undergone COVID-19 testing. Of the reported household deaths, 47.2% (982 individuals) experienced CLS/ILS 2 weeks before their death.

conclusionTelephonic surveillance indicated that the number of SARS-CoV-2 cases was at least twice as high as the number of confirmed cases in Malawi. Our findings also suggest a substantial under-reporting of SARS-CoV-2-related deaths. Telephonic surveillance has proven feasible in Malawi, achieving the ability to characterise SARS-CoV-2 morbidity and mortality trends in low-resource settings.

Indexed as

COVID-19SARS-CoV-2TelephoneAdolescentAdultAgedFemaleHumansMalawiMaleMiddle AgedPandemicsSentinel SurveillanceSurveys and QuestionnairesYoung AdultCOVID-19Cross-sectional surveyGlobal HealthPublic HealthSARS

Identifiers

PMID38754899
PMCPMC11097830

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.