SEIR model for COVID-19 dynamics incorporating the environment and social distancing

Mwalili, Samuel; Kimathi, Mark; Ojiambo, Viona; Gathungu, Duncan; Mbogo, Rachel Waema

doi:10.21203/rs.3.rs-19249/v2

Cited by 17 publications

(28 citation statements)

References 2 publications

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“…Then [5] predicted COVID-19 in Indonesia based on early endemic data using Richard's curve. Other models and predictions using statistical approaches [6][7][8][9][10] or those using SIR, SEIR, and their extensions [11][12][13][14][15][16] have been widely performed. Moreover, some researchers used fractional order in epidemic models to model the spread of COVID-19.…”

Section: Introductionmentioning

confidence: 99%

An SIR epidemic model for COVID-19 spread with fuzzy parameter: the case of Indonesia

et al. 2021

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The aim of this research is to construct an SIR model for COVID-19 with fuzzy parameters. The SIR model is constructed by considering the factors of vaccination, treatment, obedience in implementing health protocols, and the corona virus-load. Parameters of the infection rate, recovery rate, and death rate due to COVID-19 are constructed as a fuzzy number, and their membership functions are used in the model as fuzzy parameters. The model analysis uses the generation matrix method to obtain the basic reproduction number and the stability of the model’s equilibrium points. Simulation results show that differences in corona virus-loads will also cause differences in the transmission of COVID-19. Likewise, the factors of vaccination and obedience in implementing health protocols have the same effect in slowing or stopping the transmission of COVID-19 in Indonesia.

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Section: Introductionmentioning

confidence: 99%

An SIR epidemic model for COVID-19 spread with fuzzy parameter: the case of Indonesia

et al. 2021

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“…The rationale underpinning these public health measures is that restricting normal activities decreases the number, duration, and proximity of interpersonal contacts and thus the potential for viral transmission. Transmission simulations using complex mathematical modelling have built on past experience such as the 1918 influenza epidemic (7), as well as assumptions about the contemporary scale and nature of contact in populations (8). However, the initial models were not always founded on empirical evidence from behavioral scientists on the feasibility or sustainability of mass social and behavior change in contemporary society.…”

Section: Introductionmentioning

confidence: 99%

How Well Does Societal Mobility Restriction Help Control the COVID-19 Pandemic? Evidence from Real-Time Evaluation

Lee

Long

et al. 2020

SSRN Journal

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Background Restrictions on mobility have been implemented by many countries to limit the spread of novel coronavirus infection (COVID-19) yet have important social and economic consequences. Their impact on reducing transmission is, however, inadequately understood. Methods We examined the association of COVID-19 incidence rates with mobility changes, defined as changes in categories of domestic location, against a pre-pandemic baseline, using country-specific daily incidence data on newly confirmed COVID-19 cases and mobility data collected from mobile devices in all 34 OECD countries plus Singapore and Taiwan. The study period was from the day of the 100th case in each country to August 31, 2020. Daily incidence rates were lagged by 14 days and regressed to mobility changes using LOESS regression and logit regression. Findings In two thirds of examined countries, reductions of up to 40% in commuting mobility (to workplaces, transit stations, retailers, and recreation) were associated with decreased COVID-19 incidence, more so early in the pandemic. However, these decreases plateaued as mobility remained low or decreased further. We found smaller or negligible associations between mobility restriction and incidence rates in the late phase in most countries. Interpretation Mild to moderate degrees of mobility restriction in most countries were associated with reduced incidence rates of COVID-19 that appear to attenuate over time, while some countries exhibited no effect of such restrictions. More detailed research is needed to precisely understand the benefits and limitations of mobility restrictions as part of the public health response to the COVID-19 pandemic. Funding none This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3706748 How well does societal mobility restriction help control the COVID-19 pandemic? Evidence from real-time evaluation

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“…Transmission simulations using complex mathematical modelling have built on past experience such as the 1918 influenza epidemic, 7 as well as assumptions about the contemporary scale and nature of contact in populations. 8 However, the initial models were not always founded on empirical evidence from behavioral scientists on the feasibility or sustainability of mass social and behavior change in contemporary society. While reductions in interpersonal contact and increases in physical distancing are known to decrease respiratory infection spread, 9 the paucity of recent examples of large-scale restrictions on mobility has limited the scope for research on their impact on transmission.…”

Section: Introductionmentioning

confidence: 99%

How well does societal mobility restriction help control the COVID-19 pandemic? Evidence from real-time evaluation

Lee

Long

et al. 2020

Preprint

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Objectives To determine the impact of restrictions on mobility on reducing transmission of COVID-19. Design Daily incidence rates lagged by 14 days were regressed on mobility changes using LOESS regression and logit regression between the day of the 100th case in each country to August 31, 2020. Setting 34 OECD countries plus Singapore and Taiwan. Participants Google mobility data were obtained from people who turned on mobile device-based global positioning system (GPS) and agreed to share their anonymized position information with Google. Interventions We examined the association of COVID-19 incidence rates with mobility changes, defined as changes in categories of domestic location, against a pre-pandemic baseline, using country-specific daily incidence data on newly confirmed COVID-19 cases and mobility data. Results In two thirds of examined countries, reductions of up to 40% in commuting mobility (to workplaces, transit stations, retailers, and recreation) were associated with decreased COVID-19 incidence, more so early in the pandemic. However, these decreases plateaued as mobility remained low or decreased further. We found smaller or negligible associations between mobility restriction and incidence rates in the late phase in most countries. Conclusion Mild to moderate degrees of mobility restriction in most countries were associated with reduced incidence rates of COVID-19 that appear to attenuate over time, while some countries exhibited no effect of such restrictions. More detailed research is needed to precisely understand the benefits and limitations of mobility restrictions as part of the public health response to the COVID-19 pandemic.

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SEIR model for COVID-19 dynamics incorporating the environment and social distancing

Cited by 17 publications

References 2 publications

An SIR epidemic model for COVID-19 spread with fuzzy parameter: the case of Indonesia

An SIR epidemic model for COVID-19 spread with fuzzy parameter: the case of Indonesia

How Well Does Societal Mobility Restriction Help Control the COVID-19 Pandemic? Evidence from Real-Time Evaluation

How well does societal mobility restriction help control the COVID-19 pandemic? Evidence from real-time evaluation

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