COVID-19 Testing Trend: A Retrospective Analysis of the Three Major Pandemic Waves in Punjab, Pakistan.
CUREUS JOURNAL OF MEDICAL SCIENCE(2024)
Akhtar Saeed Med & Dent Coll | Univ Lahore | Bakhtawar Amin Med & Dent Coll
Abstract
Background/objectives: There is some evidence in the literature of under-testing of COVID-19 cases in Pakistan. This study aims to explore COVID-19 testing trends and the factors affecting them in a lower middle-income country for future infectious disease policy-making and intervention strategies. Methodology: The study was conducted as a serial cross-sectional study during the three major peaks from March 2020 to June 2021 on 1616 participants in Punjab, Pakistan. This is the first study to explore COVID-19 testing trends in association with flu-like symptoms (FLS) and the factors affecting all three major waves in Pakistan. Results: The results show that in all three waves, only 18.8% reported COVID-19 tested despite that 86.7% thought they had already had COVID-19, with 51.3% reporting having FLS and 35.6% with exposure to FLS from their families and 19.8% of positive testing rate among their family members. Out of the survey participants, 66% received vaccination, and over 80% had their eligible family members immunized. Fear of contracting COVID-19 was 69.7% in all three waves. Factors positively associated with the uptake of testing were the age group of 31-40 years with an adjusted odds ratio of 3.27 (95% confidence interval (CI): 2.09-5.12) for the second wave and an adjusted odds ratio of 13.75 (95% CI: 9.43-20.01) for the third wave and traveling abroad with odds of 3.08 times when the reference was inland traveling. The adjusted odds ratio to test for FLS was 1.62 (95% CI: 1.21-2.16). Conclusion: In this study, there is convincing evidence of COVID-19 under-testing and thus under-reporting. This study also suggests that fear-based interventions may be counterproductive; however, economic factors such as education, employment, and traveling are significant in guiding the behavior for infectious disease prevention and management.
MoreTranslated text
Key words
pakistan,lower middle income countries,pandemic,testing trend,covid-19,infectious disease
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
2020
被引用37 | 浏览
2021
被引用74 | 浏览
2021
被引用161 | 浏览
2021
被引用157 | 浏览
2016
被引用755 | 浏览
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest