A SIR-Poisson Model for COVID-19: Evolution and Transmission Inference in the Maghreb Central Regions

Hassen, Hanen Ben; Elaoud, Anis; Salah, Nahla Ben; Masmoudi, Afif

doi:10.1007/s13369-020-04792-0

Cited by 23 publications

(17 citation statements)

References 24 publications

(27 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The scholarly literature on the effects of the COVID-19 pandemic on food systems and consumption patterns has been so far mostly geographically biased; it focuses on Western and Southern Europe, North America, and China (30), while developing countries in general and those of the NENA region in particular, such as Morocco, have been overlooked. The analysis of the scholarly literature shows that most of the papers dealing with the COVID-19 emergency in Morocco focus on the dynamics of the spread of the virus as well as its health impacts (44)(45)(46)(47)(48)(49)(50)(51)(52)(53)(54)(55)(56)(57)(58). Other articles analyze the pandemic's socio-economic impacts in the kingdom (45,59).…”

Section: Introductionmentioning

confidence: 99%

Exploring Household Food Dynamics During the COVID-19 Pandemic in Morocco

et al. 2021

View full text Add to dashboard Cite

Alongside the dramatic impact on health systems, eating, shopping, and other food-related habits may have been affected by the COVID-19 crisis. This paper analyses the impacts of the COVID-19 pandemic on food shopping habits and food-related activities of a diverse sample of 340 adult consumers in Morocco. The study is based on an online survey conducted in Morocco from September 15 to November 5, 2020, utilizing a standardized questionnaire delivered in French and Arabic via Survey Monkey. The findings show that consumers' diet, shopping behavior, and food interactions have changed significantly. Indeed, the survey outcomes indicated (i) an increase in the consumption of local items owing to food safety concerns; (ii) an increase in online grocery shopping; (iii) a rise in panic buying and food hoarding; and (iv) an increase in culinary capabilities. The findings are expected to help guide Morocco's current emergency measures as well as long-term food-related policies.

show abstract

Section: Introductionmentioning

confidence: 99%

Exploring Household Food Dynamics During the COVID-19 Pandemic in Morocco

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Let

denote the number of infected cases in state r at time point t with

. Usually,

is assumed to follow a Poisson distribution [ 22 , 23 , 24 ]. Since the number of infected cases in each state is hardly totally observed (i.e., the existence of heterogeneity for different states), employing the Poisson assumption could underestimate the underlying dispersion.…”

Section: Development Of the Modelmentioning

confidence: 99%

Analysis of the Spread of COVID-19 in the USA with a Spatio-Temporal Multivariate Time Series Model

Rui

Tian

Tang

et al. 2021

IJERPH

View full text Add to dashboard Cite

With the rapid spread of the pandemic due to the coronavirus disease 2019 (COVID-19), the virus has already led to considerable mortality and morbidity worldwide, as well as having a severe impact on economic development. In this article, we analyze the state-level correlation between COVID-19 risk and weather/climate factors in the USA. For this purpose, we consider a spatio-temporal multivariate time series model under a hierarchical framework, which is especially suitable for envisioning the virus transmission tendency across a geographic area over time. Briefly, our model decomposes the COVID-19 risk into: (i) an autoregressive component that describes the within-state COVID-19 risk effect; (ii) a spatiotemporal component that describes the across-state COVID-19 risk effect; (iii) an exogenous component that includes other factors (e.g., weather/climate) that could envision future epidemic development risk; and (iv) an endemic component that captures the function of time and other predictors mainly for individual states. Our results indicate that maximum temperature, minimum temperature, humidity, the percentage of cloud coverage, and the columnar density of total atmospheric ozone have a strong association with the COVID-19 pandemic in many states. In particular, the maximum temperature, minimum temperature, and the columnar density of total atmospheric ozone demonstrate statistically significant associations with the tendency of COVID-19 spreading in almost all states. Furthermore, our results from transmission tendency analysis suggest that the community-level transmission has been relatively mitigated in the USA, and the daily confirmed cases within a state are predominated by the earlier daily confirmed cases within that state compared to other factors, which implies that states such as Texas, California, and Florida with a large number of confirmed cases still need strategies like stay-at-home orders to prevent another outbreak.

show abstract

“…Epidemiological studies have established prediction models based on existing data (Zhou et al 2020 ) and have identified the phenomenon of human transmission in China (Riou and Althaus 2020 ). Hassen et al ( 2021 ) proposed a susceptible–infectious–removed (SIR)–Poisson model to predict the range of future infections. Hoch et al ( 2018 ), meanwhile, established a susceptible–infectious–removed–susceptible (SIRS) model to simulate dynamic infection in a multigroup system.…”

Section: Introductionmentioning

confidence: 99%

System dynamics analysis of COVID-19 prevention and control strategies

Jia

Fang

2021

Environ Sci Pollut Res

View full text Add to dashboard Cite

The COVID-19 pandemic now affects the entire world and has many major effects on the global economy, environment, health, and society. Focusing on the harm COVID-19 poses for human health and society, this study used system dynamics to establish a prevention and control model that combines material supply, public opinion dissemination, public awareness, scientific and technological research, staggered work shifts, and the warning effect (of law/policy). Causal loop analysis was used to identify interactions between subsystems and explore the key factors affecting social benefit. Further, different scenarios were dynamically simulated to explore optimal combination modes. The main findings were as follows: (1) The low supervision mode will produce a lag effect and superimposed effect on material supply and impede social benefit. (2) The strong supervision mode has multiple performances; it can reduce online public opinion dissemination and the rate of concealment and false declaration and improve government credibility and social benefit. However, a fading effect will appear in the middle and late periods, and over time, the effect of strong supervision will gradually weaken (but occasionally rebound) and thus require adjustment. These findings can provide a theoretical basis for improving epidemic prevention and control measures.

show abstract

A SIR-Poisson Model for COVID-19: Evolution and Transmission Inference in the Maghreb Central Regions

Cited by 23 publications

References 24 publications

Exploring Household Food Dynamics During the COVID-19 Pandemic in Morocco

Exploring Household Food Dynamics During the COVID-19 Pandemic in Morocco

Analysis of the Spread of COVID-19 in the USA with a Spatio-Temporal Multivariate Time Series Model

System dynamics analysis of COVID-19 prevention and control strategies

Contact Info

Product

Resources

About