Limitations of COVID-19 testing and case data for evidence-informed health policy and practice

Cross-Sectional Survey of Factors Contributing to COVID-19 Testing Hesitancy Among US Adults at Risk of Severe Outcomes from COVID-19

INTRODUCTION

The United States Centers for Disease Control and Prevention (CDC) advises testing individuals for COVID-19 after exposure or if they display symptoms. However, a deeper understanding of demographic factors associated with testing hesitancy is necessary.

METHODS

A US nationwide cross-sectional survey of adults with risk factors for developing severe COVID-19 ("high-risk" individuals) was conducted from August 18-September 5, 2023. Objectives included characterizing demographics and attitudes associated with COVID-19 testing. Inverse propensity weighting was used to weight the data to accurately reflect the high-risk adult US population as reflected in IQVIA medical claims data. We describe here the weighted results modeled to characterize demographic factors driving hesitancy.

RESULTS

In the weighted sample of 5019 respondents at high risk for severe COVID-19, 58.2% were female, 37.8% were ≥ 65 years old, 77.1% were White, and 13.9% had a postgraduate degree. Overall, 67% were Non-testers (who indicated that they were unlikely or unsure of their likelihood of being tested within the next 6 months); these respondents were significantly more likely than Testers (who indicated a higher probability of testing within 6 months) to be female (60.2 vs. 54.1%; odds ratio [OR] [95% confidence interval (CI)], 1.3 [1.1‒1.4]), aged ≥ 65 years old (41.5 vs. 30.3%; OR [95% CI] compared with ages 18‒34 years, 0.6 [0.5‒0.7]), White (82.1 vs. 66.8%; OR [95% CI], 1.4 [1.1‒1.8]), and to identify as politically conservative (40.9 vs. 18.1%; OR [95% CI], 2.6 [2.3‒2.9]). In contrast, Testers were significantly more likely than Non-testers to have previous experience with COVID-19 testing, infection, or vaccination; greater knowledge regarding COVID-19 and testing; greater healthcare engagement; and concerns about COVID-19.

CONCLUSIONS

Older, female, White, rural-dwelling, and politically conservative high-risk adults are the most likely individuals to experience COVID-19 testing hesitancy. Understanding these demographic factors will help guide strategies to improve US testing rates.

Are self-test kits still relevant post COVID-19 pandemic? Qualitative study on working adults' perceptions

BACKGROUND

Other than self-isolation measures, self-testing is likely to reduce the transmission of COVID-19 and may become a valuable approach in future outbreaks of infectious diseases. This study delves into the perceptions and experiences of working adults who utilised COVID-19 self-test kits in Singapore during the post-pandemic period.

METHODS

Employing a qualitative descriptive design, in-depth interviews were conducted with 40 working adults from diverse occupations, with a median age of 35 years. Thematic analysis of transcribed interviews was carried out by two independent qualitative research-trained researchers.

RESULTS

Facilitators included personal motivations like safeguarding vulnerable individuals and the convenience of user-friendly self-test kits. Proximal environmental factors encompassed situations involving close contacts and large gatherings, while distal factors involved workplace regulations, public health campaigns, mass media influence, and trust in authorised kits. Nonetheless, barriers include discomfort, cost, uncertainty about proper technique, and evolving testing requirements. Positive test results prompted participants to notify contacts and self-isolate, whereas negative results encouraged a return to normalcy. Participants recommend sustained testing for new variants and vulnerable groups, though some view it as unnecessary due to pandemic normalisation.

CONCLUSIONS

Self-testing emerged as a social phenomenon influenced by societal obligations and relationships across multiple levels. Effective communication strategies may play a role in fostering trust and ensuring that working adults sustain the practice of self-testing; therefore, further research is needed to explore their potential impact. Such efforts could be valuable for maintaining vigilance and achieving effective disease control in the post-COVID-19 pandemic landscape.

Socioeconomic and Demographic Effects on SARS-CoV-2 Testing: Evidence From the State of Uttar Pradesh, India

Background The rapid global spread of SARS-CoV-2 highlighted critical challenges in healthcare systems worldwide, with differences in testing access and utilization becoming particularly evident. This study investigates the socioeconomic and demographic factors influencing SARS-CoV-2 testing service access and utilization during the second wave of the pandemic in Uttar Pradesh (UP), India. Methods The study was conducted from July to October 2023 in two districts of Uttar Pradesh (UP). These districts were chosen because one had the highest and the other the lowest SARS-CoV-2 testing rates per million population as reported from March to June 2021. The study population included consenting adult individuals with self-reported symptoms indicative of SARS-CoV-2 infection during March-June 2021. The study excluded individuals under 18 years, those who did not consent, pregnant or lactating mothers, and those with communication-impairing medical conditions. Data were collected using a structured questionnaire based on Andersen's Behavioural Model of Health Services Use. We used chi-squared tests for all categorical variables to obtain p-values and Poisson regression to identify factors influencing testing rates. Results We screened 4,595 individuals and identified 675 eligible participants for this study. Adjusted prevalence ratios derived from multiple variate Poisson regression models showed that participants in Sitapur had a 0.47 (95% CI: 0.39-0.57) times the prevalence of being tested than those in Lucknow. Furthermore, individuals from other backward castes and scheduled castes had a 1.15 (95% CI: 0.99-1.34) and 1.22 (95% CI: 0.95-1.56) times prevalence of being tested for SARS-CoV-2, respectively, when compared to the general caste population. Scheduled Tribes showed a higher prevalence of being tested, contrasting with existing literature. Households with low, middle, and high income showed a 1.46 (95% CI: 1.12-1.89), 1.52 (95% CI: 1.14-2.02), and 1.73 (95% CI: 1.23-2.45) times the prevalence of SARS-CoV-2 testing compared to those below the poverty line, respectively. Behavioral factors such as media use showed an inverse relationship with testing prevalence; individuals who did not watch TV at all had a 0.83 (95% CI: 0.70-0.99) times prevalence of being tested compared to frequent viewers, and similarly, those not using the internet on mobiles had a 0.82 (95% CI: 0.67-0.99) times prevalence than daily users. Individuals using private healthcare facilities had a 0.87 (95% CI: 0.77-0.99) times prevalence of SARS-CoV-2 testing compared to those using government facilities. Conclusions These findings highlight the importance of public health strategies that address socio-economic and behavioral disparities to ensure equitable testing access across all community groups.

Economic Evaluation of COVID-19 Screening Tests and Surveillance Strategies in Low-Income, Middle-Income, and High-Income Countries: A Systematic Review

BACKGROUND Economic evaluation of the testing strategies to control transmission and monitor the severity of COVID-19 after the pandemic is essential. This study aimed to review the economic evaluation of COVID-19 tests and to construct a model with outcomes in terms of cost and test acceptability for surveillance in the post-pandemic period in low-income, middle-income, and high-income countries. MATERIAL AND METHODS We performed the systematic review following PRISMA guidelines through MEDLINE and EMBASE databases. We included the relevant studies that reported the economic evaluation of COVID-19 tests for surveillance. Also, we input current probability, sensitivity, and specificity for COVID-19 surveillance in the post-pandemic period. RESULTS A total of 104 articles met the eligibility criteria, and 8 articles were reviewed and assessed for quality. The specificity and sensitivity of COVID-19 screening tests were reported as 80% to 90% and 40% to 90%, respectively. The target population presented a mortality rate between 0.2% and 19.2% in the post-pandemic period. The implementation model of COVID-19 screening tests for surveillance with a cost mean for molecular and antigen tests was US$ 46.64 (min-max US $0.25-$105.39) and US $6.15 (min-max US $2-$10), respectively. CONCLUSIONS For the allocation budget for the COVID-19 surveillance test, it is essential to consider the incidence and mortality of the post-pandemic period in low-income, middle-income, and high-income countries. A robust method to evaluate outcomes is needed to prevent increasing COVID-19 incidents earlier.

Forecasting daily COVID-19 cases with gradient boosted regression trees and other methods: evidence from U.S. cities

Introduction

There is a vast literature on the performance of different short-term forecasting models for country specific COVID-19 cases, but much less research with respect to city level cases. This paper employs daily case counts for 25 Metropolitan Statistical Areas (MSAs) in the U.S. to evaluate the efficacy of a variety of statistical forecasting models with respect to 7 and 28-day ahead predictions.

Methods

This study employed Gradient Boosted Regression Trees (GBRT), Linear Mixed Effects (LME), Susceptible, Infectious, or Recovered (SIR), and Seasonal Autoregressive Integrated Moving Average (SARIMA) models to generate daily forecasts of COVID-19 cases from November 2020 to March 2021.

Results

Consistent with other research that have employed Machine Learning (ML) based methods, we find that Median Absolute Percentage Error (MAPE) values for both 7-day ahead and 28-day ahead predictions from GBRTs are lower than corresponding values from SIR, Linear Mixed Effects (LME), and Seasonal Autoregressive Integrated Moving Average (SARIMA) specifications for the majority of MSAs during November-December 2020 and January 2021. GBRT and SARIMA models do not offer high-quality predictions for February 2021. However, SARIMA generated MAPE values for 28-day ahead predictions are slightly lower than corresponding GBRT estimates for March 2021.

Discussion

The results of this research demonstrate that basic ML models can lead to relatively accurate forecasts at the local level, which is important for resource allocation decisions and epidemiological surveillance by policymakers.

Public's Willingness to Perform COVID-19 Self-Testing During the Transition to the Endemic Phase in Malaysia - A Population-Based Cross-Sectional Study

Introduction

Malaysia entered the transition to the endemic phase of Coronavirus 2019 (COVID-19) on 1st April 2022. This study aims to determine the public's willingness to perform COVID-19 self-testing. Factors that influenced their willingness were also assessed.

Methods

A nationwide, cross-sectional, and population-based study was conducted online in Malaysia from 28th April 2023 to 4th June 2023. Individuals aged 18 years and above were enrolled through the snowball sampling method. Data were analyzed by using the Chi-Square test, independent t-test, and binary logistic regression.

Results

One thousand four hundred fifty-three responses were included in the analysis. Of these respondents, 89.3% were willing, 4.1% were reluctant, and 6.6% remained hesitant to perform COVID-19 self-testing, The common reasons given by those willing to perform COVID-19 self-testing included being able to self-isolate (99.0%) and seek treatment (96.3%) earlier if tested positive. The common reasons against COVID-19 self-testing included the belief that COVID-19 is equivalent to the common flu (91.7%) and having received the COVID-19 vaccine (78.3%). The isolation policy for COVID-19 was the most significant consideration for those who were still hesitant (85.4%). Women [adjusted odds ratios (OR): 2.1, 95% confidence intervals (95% CI): 1.44-3.00, p < 0.001], individuals with tertiary education (OR: 2.1, 95% CI: 1.32-3.26, p = 0.002), those vaccinated against COVID-19 (OR: 8.1, 95% CI: 2.63-24.82, p < 0.001), and individuals with prior experience of COVID-19 self-testing (OR: 4.2, 95% CI: 2.84-6.12, p < 0.001) showed a significantly higher willingness to engage in COVID-19 self-testing.

Conclusion

The public exhibited a high willingness to perform COVID-19 self-testing during the transition to the endemic phase in Malaysia. Future strategies to promote COVID-19 self-testing uptake in Malaysia should focus on vulnerable groups, address the common concerns among those hesitant and reluctant, and highlight the advantages of COVID-19 self-testing.

Detection of SARS-CoV-2 RNA in wastewater from dormitory buildings in a university campus: comparison with individual testing results

Wastewater-based epidemiology (WBE) for monitoring COVID-19 has been largely used to detect the spread of the disease at the community level. From February to December 2022, we collected 24-h composite sewage samples from dormitory buildings in George Mason University (Fairfax, Virginia, USA) housing approximately 5,200 resident students. SARS-CoV-2 RNA extraction was achieved using an automated system based on magnetic nanoparticles. Analysis of SARS-CoV-2 RNA was performed using reverse transcription quantitative PCR based on the Centers for Disease Control and Prevention (CDC) N1 and N2 assays. From the 362 samples collected, 86% showed positive detection of SARS-CoV-2 RNA. Wastewater monitoring was able to detect SARS-CoV-2 RNA in 96% of the samples from buildings housing students with COVID-19. Over the period of study, we observed significant correlations between the SARS-CoV-2 concentration (copy number mL-1) in wastewater and the number of positive cases on campus based on individual saliva testing. Although several reports have been published on the wastewater monitoring of COVID-19 in university campuses, our study is one of the very few that provides results that were obtained during the last phase of the pandemic (roughly the year 2022), when the large majority of students were vaccinated and back on campus.