ArticleBMC infectious diseases2021
Factors shaping the COVID-19 epidemic curve: a multi-country analysis.
Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Article
- Five Years of COVID-19 in Tocantins, Brazil: Epidemiology, Vaccination Impact, and SARS-CoV-2 Genomic Dynamics (2020-2025).Viruses · 2025Article
- The clinical and economic costs associated with regional disparities in varicella vaccine coverage in Italy over 50 years (2020-2070).Scientific reports · 2024Article
- ModInterv COVID-19: An online platform to monitor the evolution of epidemic curves.Applied soft computing · 2023Article
- Exploring the Role of Infodemics in People's Incompliance with Preventive Measures during the COVID-19 in Conflict Settings (Mixed Method Study).Healthcare (Basel, Switzerland) · 2023Article
- Travel behaviour changes and risk perception during COVID-19: A case study of Malaysia.Transportation research interdisciplinary perspectives · 2023Article
- Multiple waves of COVID-19: a pathway model approach.Nonlinear dynamics · 2023Article
- Trends in rifampicin resistance among patients with presumptive TB in the pre-COVID and COVID-era.Journal of clinical tuberculosis and other mycobacterial diseases · 2022Article
- Exploring Socioeconomic Status as a Global Determinant of COVID-19 Prevalence, Using Exploratory Data Analytic and Supervised Machine Learning Techniques: Algorithm Development and Validation Study.JMIR formative research · 2022Article
- Discrete Models in Epidemiology: New Contagion Probability Functions Based on Real Data Behavior.Bulletin of mathematical biology · 2022Article
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14 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundLockdown measures are the backbone of containment measures for the COVID-19 pandemic both in high-income countries (HICs) and low- and middle-income countries (LMICs). However, in view of the inevitably-occurring second and third global covid-19 wave, assessing the success and impact of containment measures on the epidemic curve of COVID-19 and people's compliance with such measures is crucial for more effective policies. To determine the containment measures influencing the COVID-19 epidemic curve in nine targeted countries across high-, middle-, and low-income nations.
methodsFour HICs (Germany, Sweden, Italy, and South Korea) and five LMICs (Mexico, Colombia, India, Nigeria, and Nepal) were selected to assess the association using interrupted time series analysis of daily case numbers and deaths of COVID-19 considering the following factors: The "stringency index (SI)" indicating how tight the containment measures were implemented in each country; and the level of compliance with the prescribed measures using human mobility data. Additionally, a scoping review was conducted to contextualize the findings.
resultsMost countries implemented quite rigorous lockdown measures, particularly the LMICs (India, Nepal, and Colombia) following the model of HICs (Germany and Italy). Exceptions were Sweden and South Korea, which opted for different strategies. The compliance with the restrictions-measured as mobility related to home office, restraining from leisure activities, non-use of local transport and others-was generally good, except in Sweden and South Korea where the restrictions were limited. The endemic curves and time-series analysis showed that the containment measures were successful in HICs but not in LMICs.
conclusionThe imposed lockdown measures are alarming, particularly in resource-constrained settings where such measures are independent of the population segment, which drives the virus transmission. Methods for examining people's movements or hardships that are caused by covid- no work, no food situation are inequitable. Novel and context-adapted approach of dealing with the COVID-19 crisis are therefore crucial.
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