ArticleInternational journal of environmental research and public health2021
Which National Factors Are Most Influential in the Spread of COVID-19?
Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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Who cites it
6 citing papers in PubMed.
- No Place to Hide? Regional Resilience and Vulnerability to Global Catastrophic Risk.Global challenges (Hoboken, NJ) · 2026Review
- A national growth mixture modeling analysis of county-level COVID-19 incidence rate trajectories and health inequities during three successive pandemic waves in 2020.Scientific reports · 2025Article
- The Influence of Metabolic Syndrome on the Development of Gastrointestinal Malignant Tumors-A Review.Medicina (Kaunas, Lithuania) · 2025Review
- Nonlinear time series analysis of state-wise COVID-19 in Malaysia using wavelet and persistent homology.Scientific reports · 2024Article
- Effectiveness of controlling COVID-19 epidemic by implementing soft lockdown policy and extensive community screening in Taiwan.Scientific reports · 2022Article
- Effects of government policies on the spread of COVID-19 worldwide.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
The outbreak of the novel COVID-19, declared a global pandemic by WHO, is the most serious public health threat seen in terms of respiratory viruses since the 1918 H1N1 influenza pandemic. It is surprising that the total number of COVID-19 confirmed cases and the number of deaths has varied greatly across countries. Such great variations are caused by age population, health conditions, travel, economy, and environmental factors. Here, we investigated which national factors (life expectancy, aging index, human development index, percentage of malnourished people in the population, extreme poverty, economic ability, health policy, population, age distributions, etc.) influenced the spread of COVID-19 through systematic statistical analysis. First, we employed segmented growth curve models (GCMs) to model the cumulative confirmed cases for 134 countries from 1 January to 31 August 2020 (logistic and Gompertz). Thus, each country's COVID-19 spread pattern was summarized into three growth-curve model parameters. Secondly, we investigated the relationship of selected 31 national factors (from KOSIS and
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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.