Factors shaping the COVID-19 epidemic curve: a multi-country analysis

BMC Infectious Diseases

Pia Oechsner¹  Martin Anto²  Ahmed Asa’ad Al-Aghbari³  Sonia Diaz-Monsalve³  Axel Kroeger³  Dhia Joseph Chackalackal³  Eduardo Andrés Alfonso-Sierra³  Tatiana Rivera Ramirez³  Maria Angelica Carrillo⁴  Rocio Cardenas-Sanchez⁵  Su Yeon Jang⁶  In-Hwan Oh⁶  Brian Kibiwott Kirui⁷  Laith Hussain-Alkhateeb⁷ 

[1] Angewandte Gesundheitswissenschaft, Ravensburg-Weingarten University, Weingarten, Germany;Bangalore, India;Centre for Medicine and Society, Albert-Ludwigs-University Freiburg, Bismarckallee (3’d floor), 79089, Freiburg, Germany;Centre for Medicine and Society, Albert-Ludwigs-University Freiburg, Bismarckallee (3’d floor), 79089, Freiburg, Germany;Grupo GIGA, Universidad Francisco de Paula Santander, San José de Cúcuta, Colombia;Centre for Medicine and Society, Albert-Ludwigs-University Freiburg, Bismarckallee (3’d floor), 79089, Freiburg, Germany;Laboratorio de Salud Pública, Instituto Departamental de Salud-IDS, Norte de Santander, Colombia;Department of Preventive Medicine, Kyung Hee University School of Medicine, Seoul, Korea;Global Health, School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Medicinaregatan 18A, 41390, Gothenburg, Sweden;

关键词: Coronavirus disease 2019;    SARS-CoV-2;    Segemented Time-series;    Lockdown;    COVID-19;    Stringency index;    Human mobility;   

DOI  :  10.1186/s12879-021-06714-3

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY