Can Self-Reported Symptoms Be Relied on for COVID-19 Screening in Low-Resource Settings?

Background: Understanding the extent of the disease penetration and assessing its impact is critical during a pandemic. However, laboratory-based COVID-19 estimation can be resource-intensive and may not be feasible during an emergency, particularly in low-resource settings. Aim: To investigate whether self-reported symptoms can be used for COVID-19 screening to estimate the burden among individuals aged 18 years and above in a rural setting. Methods: A community-based cross-section study was conducted in a rural district of Haryana, a state in north India, using a self-reported semi-structured questionnaire developed on a digital platform. Information on COVID-19 manifestations as essential and non-essential, confirmed laboratory tests, and disability data using Washington Groups of Short Set were obtained. The sensitivity of the COVID-19 symptoms was estimated against laboratory-confirmed true positives. A chi-square or Fisher exact test for association and a multivariable regression to determine the predictors of the prevalence was carried out. Results: In total, 2954 respondents (79.8%), out of 3700 enumerated, were interviewed. The mean age of respondents was 42 years (SD 17.2), with 54.8% female respondents. The prevalence of COVID-19 based on self-reported symptoms was 6.2% (95%CI: 5.3–7.1). The age-adjusted prevalence was 6.04% (95%CI: 5.9–6.1). Of the total COVID-19 cases, 170 (5.7%, 95%CI: 4.9–6.5) revealed a laboratory-confirmed test. Given three essential symptoms to declare provisionally COVID-19 cases, the sensitivity was 82.9% (141/170), but considering two or more essential symptoms along with two or more non-essential, the sensitivity reached up to 91.8% (156/170). The multivariable analysis showed that increased age, higher education attainment, students, entrepreneurs, persons working in private sectors, and participants with poor hygiene were predictors. Conclusions: A symptoms-based identification of COVID-19 cases can give a reliable estimate and valuable insight into the extent of the penetration, especially in low-middle-income countries, and can be a supplement, not a replacement, to a laboratory test.

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Journal
COVID
Published
2025-01-27
DOI
https://doi.org/10.3390/covid5020015
Citations
1
Primary Topic
Long-Term Effects of COVID-19
Type
article
Field-Weighted Citation Impact
1.39

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article

Can Self-Reported Symptoms Be Relied on for COVID-19 Screening in Low-Resource Settings?

Neiwete Lomi, Yashdeep Gupta, Garima Goel, Animesh Ray et al.
1 citations
COVID
Long-Term Effects of COVID-19
1.39
article

Can Self-Reported Symptoms Be Relied on for COVID-19 Screening in Low-Resource Settings?

Neiwete Lomi, Yashdeep Gupta, Garima Goel, Animesh Ray, Yatan Pal Singh Balhara, Suraj Singh Senjam
article en
1 citations

Abstract

Background: Understanding the extent of the disease penetration and assessing its impact is critical during a pandemic. However, laboratory-based COVID-19 estimation can be resource-intensive and may not be feasible during an emergency, particularly in low-resource settings. Aim: To investigate whether self-reported symptoms can be used for COVID-19 screening to estimate the burden among individuals aged 18 years and above in a rural setting. Methods: A community-based cross-section study was conducted in a rural district of Haryana, a state in north India, using a self-reported semi-structured questionnaire developed on a digital platform. Information on COVID-19 manifestations as essential and non-essential, confirmed laboratory tests, and disability data using Washington Groups of Short Set were obtained. The sensitivity of the COVID-19 symptoms was estimated against laboratory-confirmed true positives. A chi-square or Fisher exact test for association and a multivariable regression to determine the predictors of the prevalence was carried out. Results: In total, 2954 respondents (79.8%), out of 3700 enumerated, were interviewed. The mean age of respondents was 42 years (SD 17.2), with 54.8% female respondents. The prevalence of COVID-19 based on self-reported symptoms was 6.2% (95%CI: 5.3–7.1). The age-adjusted prevalence was 6.04% (95%CI: 5.9–6.1). Of the total COVID-19 cases, 170 (5.7%, 95%CI: 4.9–6.5) revealed a laboratory-confirmed test. Given three essential symptoms to declare provisionally COVID-19 cases, the sensitivity was 82.9% (141/170), but considering two or more essential symptoms along with two or more non-essential, the sensitivity reached up to 91.8% (156/170). The multivariable analysis showed that increased age, higher education attainment, students, entrepreneurs, persons working in private sectors, and participants with poor hygiene were predictors. Conclusions: A symptoms-based identification of COVID-19 cases can give a reliable estimate and valuable insight into the extent of the penetration, especially in low-middle-income countries, and can be a supplement, not a replacement, to a laboratory test.

COVIDVol. 5(2)
All India Institute of Medical Sciences (IN)
Indian Council of Medical Research
Openalex Percentile: Top 24%
Long-Term Effects of COVID-19
1.39
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