Evidence map›Paper›PMID 37845641›Full record

ArticleBMC infectious diseases2023

Comparison of Influenza-Like Illness (ILI) incidence data from the novel LeCellPHIA participatory surveillance system with COVID-19 case count data, Lesotho, July 2020 - July 2021.

Sarah D Francis, Gerald Mwima, Molibeli Lethoko, Christiana Chang, Shannon M Farley, Fred Asiimwe, Qixuan Chen, Christine West, Abigail R Greenleaf

Abstract read
In one paragraph

Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Sarah D FrancisDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, USA. sld2167@cumc.columbia.edu.
Gerald MwimaICAP at Lesotho, Maseru, Lesotho.
Molibeli LethokoICAP at Lesotho, Maseru, Lesotho.
Christiana ChangICAP at Columbia, New York, USA.
Shannon M FarleyICAP at Columbia, New York, USA.
Fred AsiimweCDC, Maseru, Lesotho.
Qixuan ChenDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, USA.
Christine WestCenters for Disease Control (CDC), Atlanta Global Health Center/Division of Global HIV and TB, Atlanta, USA.
Abigail R GreenleafICAP at Columbia, New York, USA.

Funding

DYnamics of Contraception in Eswatini (DYCE)K01HD108636 · NICHD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Abigail Regan Greenleaf · 2023 to 2026
$522k
ACL HHS U01GH002171CDC HHS #6 NU2GGH002171-03-00CGH CDC HHS U01 GH002171NICHD NIH HHS K01 HD108636
6 · The paper itself

Abstract

backgroundWhile laboratory testing for infectious diseases such as COVID-19 is the surveillance gold standard, it is not always feasible, particularly in settings where resources are scarce. In the small country of Lesotho, located in sub-Saharan Africa, COVID-19 testing has been limited, thus surveillance data available to local authorities are limited. The goal of this study was to compare a participatory influenza-like illness (ILI) surveillance system in Lesotho with COVID-19 case count data, and ultimately to determine whether the participatory surveillance system adequately estimates the case count data.

methodsA nationally-representative sample was called on their mobile phones weekly to create an estimate of incidence of ILI between July 2020 and July 2021. Case counts from the website Our World in Data (OWID) were used as the gold standard to which our participatory surveillance data were compared. We calculated Spearman's and Pearson's correlation coefficients to compare the weekly incidence of ILI reports to COVID-19 case count data.

resultsOver course of the study period, an ILI symptom was reported 1,085 times via participatory surveillance for an average annual cumulative incidence of 45.7 per 100 people (95% Confidence Interval [CI]: 40.7 - 51.4). The cumulative incidence of reports of ILI symptoms was similar among males (46.5, 95% CI: 39.6 - 54.4) and females (45.1, 95% CI: 39.8 - 51.1). There was a slightly higher annual cumulative incidence of ILI among persons living in peri-urban (49.5, 95% CI: 31.7 - 77.3) and urban settings compared to rural areas. The January peak of the participatory surveillance system ILI estimates correlated significantly with the January peak of the COVID-19 case count data (Spearman's correlation coefficient = 0.49; P < 0.001) (Pearson's correlation coefficient = 0.67; P < 0.0001).

conclusionsThe ILI trends captured by the participatory surveillance system in Lesotho mirrored trends of the COVID-19 case count data from Our World in Data. Public health practitioners in geographies that lack the resources to conduct direct surveillance of infectious diseases may be able to use cell phone-based data collection to monitor trends.

Indexed as

Communicable DiseasesCOVID-19Influenza, HumanVirus DiseasesCOVID-19 TestingFemaleHumansIncidenceLesothoMaleCOVID-19Influenza-like-IllnessParticipatory surveillance

Identifiers

PMID37845641
PMCPMC10577929

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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.