A model of COVID-19 transmission to understand the effectiveness of the containment measures: application to data from France

Zongo, Pascal; Zorom, Malicki; Mophou, Gisèle; Dorville, René; Beaumont, Catherine

doi:10.1017/s0950268820002162

Cited by 6 publications

(7 citation statements)

References 29 publications

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“…We expect a direct and negative effect of stringent containment measures on Covid-19-related mortality, since after a certain amount of time- stringent measures lead to decreased contagions, hence, lower mortality (H1) . During the first year of the pandemic, we increasingly see evidence showing a negative relation between government interventions through containment policies and the spread of the virus ( Deb et al, 2020 ; Dehning et al, 2020 ; Zongo et al, 2020 ), so it is plausible to infer that this will also affect mortality. In this article, we will focus on testing the interaction between policy and trust in government, on the desired outcome of that policy (in our case: low mortality).…”

Section: Public Policy Guidelines and Trust During The Pandemicmentioning

confidence: 99%

In trust we trust: The impact of trust in government on excess mortality during the COVID-19 pandemic

Zaki

Nicoli

Wayenberg

et al. 2022

Public Policy and Administration

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The COVID-19 pandemic has brought forward myriad challenges to public policy, central of which is understanding the different contextual factors that can influence the effectiveness of policy responses across different systems. In this article, we explore how trust in government can influence the ability of COVID-19 policy responses to curb excess mortality during the pandemic. Our findings indicate that stringent policy responses play a central role in curbing excess mortality. They also indicate that such relationship is not only influenced by systematic and structural factors, but also by citizens’ trust in government. We leverage our findings to propose a set of recommendations for policymakers on how to enhance crisis policymaking and strengthen the designs of the widely used underlying policy learning processes.

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Section: Public Policy Guidelines and Trust During The Pandemicmentioning

confidence: 99%

In trust we trust: The impact of trust in government on excess mortality during the COVID-19 pandemic

Zaki

Nicoli

Wayenberg

et al. 2022

Public Policy and Administration

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“…Yet, this spread slowed down following the early introduction of international travel restrictions. Furthermore, ongoing transmission and increasing mobility led to the emergence and spread of many variants within the continent (Wilkinson et al, 2021 ; Zongo et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

“…The relatively low number of cases and deaths due to COVID-19 is thought to be largely attributed to the fact that forecast regarding the evolution of the pandemic in Africa has been made without regard to some specificities such as socio-demographic aspects (Zongo et al, 2020 ). African countries seem to be more resilient to COVID-19 because of the swift adoption of mitigation measures, the low rate of urbanization, the limited transport network and the youth of the population: in fact, the median age of the population lies between 31 to 42 years old for Europe, America, Oceania and Asia, as compared to 18 years old for Africa (Adams et al, 2021 ; Desjardins, 2019 ; Lulbadda et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Understanding the COVID-19 pandemic prevalence in Africa through optimal feature selection and clustering: evidence from a statistical perspective

Sidibé

Yonaba

Fowé

et al. 2022

Environ Dev Sustain

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The COVID-19 pandemic, which outbroke in Wuhan (China) in December 2019, severely hit almost all sectors of activity in the world as a consequence of the restrictive measures imposed. Two years later, Africa still emerges as the least affected continent by the pandemic. This study analyzed COVID-19 prevalence across African countries through country-level variables prior to clustering. Using Spearman-rank correlation, multicollinearity analysis and univariate filtering, 9 country-level variables were identified from an initial set of 34 variables. These variables relate to socioeconomic status, population structure, healthcare system and environment and the climatic setting. A clustering of the 54 African countries is further carried out through the use of agglomerative hierarchical clustering (AHC) method, which generated 3 distinctive clusters. Cluster 1 (11 countries) is the most affected by COVID-19 (median of 63,508.6 confirmed cases and 946.5 deaths per million) and is composed of countries with the highest socioeconomic status. Cluster 2 (27 countries) is the least affected (median of 4473.7 confirmed cases and 81.2 deaths per million), and mainly features countries with the least socioeconomic features and international exposure. Cluster 3 (16 countries) is intermediate in terms of COVID-19 prevalence (median of 2569.3 confirmed cases and 35.7 deaths per million) and features countries the least urbanized and geographically close to the equator, with intermediate international exposure and socioeconomic features. These findings shed light on the main features of COVID-19 prevalence in Africa and might help refine effectively coping management strategies of the ongoing pandemic. Supplementary Information The online version contains supplementary material available at 10.1007/s10668-022-02646-3.

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“…Кроме того, в 2020 г. в Российской Федерации зарегистрированы две вакцины для взрослых лиц от 18 до 60 лет, индуцирующие формирование гуморального и клеточного иммунитета в отношении SARS-CoV-2: комбинированная векторная вакцина («Гам-КОВИД-Вак») и вакцина на основе пептидных антигенов («ЭпиВакКорона»). В настоящее время наиболее эффективным способом снижения интенсивности эпидемического процесса COVID-19 является принятие на государственном уровне 14-дневного карантина или обсервации людей с положительными результатами исследований на наличие РНК SARS-CoV-2, социального дистанцирования и других ограничительных мер, которые широко применяются правительствами различных стран [8][9][10][11][12][13].…”

Section: обоснованиеunclassified

Characteristics of the COVID-19 Epidemiological Situation in the Russian Federation in 2020

Акимкин¹,

Кузин²,

Semenenko³

et al. 2021

Annals RAMS

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Background.The COVID-19 epidemic in the Russian Federation, which began in March 2020, caused serious damage to health of the population and led to severe economic losses. By December 28, 2020, 3 078 035 cases of COVID-19 and 55 265 lethal outcomes were registered in the country. The population of all territorial subjects of the country is involved in the epidemic process of COVID-19. The severe epidemiological situation made it necessary to conduct an analysis to identify the factors that determine the high intensity of the epidemic process, as well as the population groups with the highest risk of SARS-CoV-2 infection. Aims to study the patterns of SARS-CoV-2 spread and the epidemiological features of the initial stage of the COVID-19 pandemic in the Russian Federation in 2020. Methods.An epidemiological analysis of the COVID-19 situation in the Russian Federation was carried out to determine the dynamics of morbidity, the gender proportion and age structure of patients, the proportion of hospitalized patients, the ratio of various forms of infection, the social and professional status of patients. Standard methods of descriptive statistics Microsoft Excel and STATISTICA 12.0 (StatSoft, USA) were used for statistical processing. The mean values were estimated with a 95% confidence interval [95% CI] (the exact Klopper Pearson method). Results.During the observation time (2020), several periods were identified in the dynamics of the new COVID-19 cases detection: the period of importation of SARS-CoV-2 and the increase in morbidity, the period of epidemic decline, the period of autumn growth, the period of sustained high incidence of COVID-19. It was found that people over 70 years of age are the group with the highest risk of infection and a more severe course of COVID-19. The presence of target contingents among social and professional groups of the population, which should include medical workers, retired person, employees of educational institutions, law enforcement agencies, transport, who require special attention and medical and social support, was shown. Conclusions.The analysis showed that the large-scale spread of COVID-19 requires in-depth epidemiological studies and the development of additional disease control measures, taking into account the dynamics of the incidence of this socially significant infection.

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A model of COVID-19 transmission to understand the effectiveness of the containment measures: application to data from France

Cited by 6 publications

References 29 publications

In trust we trust: The impact of trust in government on excess mortality during the COVID-19 pandemic

In trust we trust: The impact of trust in government on excess mortality during the COVID-19 pandemic

Understanding the COVID-19 pandemic prevalence in Africa through optimal feature selection and clustering: evidence from a statistical perspective

Characteristics of the COVID-19 Epidemiological Situation in the Russian Federation in 2020

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