ArticleBMJ public health2023
Assessing health impact of COVID-19 and associated household socioeconomic factors in Papua New Guinea: evidence from the Comprehensive Health and Epidemiological Surveillance System.
Article in BMJ public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The COVID-19 pandemic had an unprecedented impact on the health and well-being of populations worldwide. Few studies have used household data to explore the health risks associated with COVID-19 in low-income and middle-income countries. This study assessed population vulnerability to COVID-19 by examining household socioeconomic factors related to COVID-19 health risks in Papua New Guinea (PNG). Methods: Using household socioeconomic surveillance data from 2020, encompassing 37 880 residents living within the catchment areas of the Comprehensive Health and Epidemiological Surveillance System, the study assessed COVID-19 health risks based on the socioeconomic demographic characteristics of the surveillance population. Multinomial logistic regression analyses were conducted to determine associated factors and to estimate predictors of COVID-19 health risks. Results: Among the surveillance population, more than 9% reported experiencing COVID-19 health risks, including home-based quarantine (9.6%), centre-based quarantine (0.5%), positive COVID-19 test (0.1%), hospitalisation due to COVID-19 (0.3%) and death from COVID-19 (0.3%). People living in semimodern houses (OR 1.47 (95% CI 1.35 to 1.61)) (verse permanent houses), individuals living in houses with 1-2 bedrooms (OR 1.12 (95% CI 1.01 to 1.25)) (verse houses with 4+ bedrooms) and those belonging to the poorest wealth quintile (OR 1.16 (95% CI 1.024 to 1.314)) (verse the richest) were more susceptible to COVID-19 health risks. Protective factors against COVID-19 health risks included urban residence (OR 0.65 (95% CI 0.59 to 0.71)) (verse rurality), aged 0-4 years (OR 0.76 (95% CI 0.64 to 0.91)) (verse aged 55+ years), households with 7-8 members (OR 0.84 (95% CI 0.74 to 0.96)) (verse 10+ members), handwashing with soap (OR 0.3 (95% CI 0.28 to 0.33)) (verse without soap). Conclusions: The study provides insights into the susceptibility to COVID-19 health risks across socioeconomic groups in PNG. These findings have implications for development of public health policies and interventions that can be extrapolated to similar settings for enhancing preparedness for future public health emergencies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.