A Model of the 2014 Ebola Epidemic in West Africa with Contact Tracing

Browne, Cameron; Xi, Hongyan; Magal, Pierre; Seydi, Moussa; Ousmanne, Seydi,; Webb, Glenn

doi:10.48550/arxiv.1410.3817

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…The parameter 𝛽 is the transmission rate of disease from susceptible to exposed. Similarly, 1/𝜎 and 1/𝛾 are the average durations of incubation and infectiousness respectively" [30,31,32,33 From III and IV we can see that I and R depends on E, so we can focus on E to have two cases, if E is zero I and R will be zero and if E, I, R, are zero that means no infection.…”

Section: 𝑁 = 𝑆 + 𝐸 + 𝐼 + 𝑅mentioning

confidence: 99%

SEIR Model on the Review Impact of Social Distancing for COVID-19 Transmission Dynamics

Madaki,

Sambo

2024

Asian Res. J. Math.

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The COVID-19 pandemic has had a huge influence on world health, with many countries enacting lockdowns and social distancing measures to help reduce transmission. However, the efficiency of these efforts is questionable, particularly in locations like as North East Nigeria, where specific socioeconomic and demographic characteristics can alter virus transmission dynamics. In this paper, we assess the pandemic in North East Nigeria by modifying the SIR to SEIR compartmental model, which incorporates data from the National Centre for Disease Control. We exposed that social distancing techniques like face masks, hand washing, and avoiding big gatherings are more successful than lockdowns in slowing the spread of COVID-19 in the region. Our findings suggest that future pandemic response plans should concentrate on social distancing measures that are both effective and feasible while avoiding the economic and social disruptions caused by lockdowns. Our work emphasizes the significance of specialized approaches to pandemic control in varied situations, including North East Nigeria.

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Section: 𝑁 = 𝑆 + 𝐸 + 𝐼 + 𝑅mentioning

confidence: 99%

SEIR Model on the Review Impact of Social Distancing for COVID-19 Transmission Dynamics

Madaki,

Sambo

2024

Asian Res. J. Math.

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“…There have been a wide range of simulation models developed for EVD in recent months to assist in decision-making and public health response efforts [6,10,[13][14][15][16][17][18][19][20][21][22], many of which are based on early models by Chowell, Legrand, and others [23][24][25]. Several models have been used for forecasting and for understanding disease dynamics [6,10,13,15], disease progression and immunity [10,22], and evaluating alternative interventions [16,26].…”

Section: Earlymentioning

confidence: 99%

Forecasting and Uncertainty in Modeling the 2014-2015 Ebola Epidemic in West Africa

Eisenberg,

D'Silva

et al. 2015

Preprint

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The 2014-2015 Ebola epidemic in West Africa is the largest ever recorded, with over 27,000 cases and 11,000 deaths as of June 2015. The public health response was challenged by difficulties with disease surveillance (particularly in more remote regions), which impacted subsequent analysis and decision-making regarding optimal interventions. We developed a stage-structured model of Ebola virus disease (EVD). A key feature of the model is that it includes a generalized correction term accounting for factors such as the fraction of cases reported and fraction of the population at risk (e.g. due to contact patterns, interventions, spatiotemporal spread, pre-existing immunity, asymptomatic cases, etc.). We generated a range of short term forecasts for Guinea, Liberia, and Sierra Leone, which we then validated using subsequent data. We also used the model to examine the uncertainty in the relative contributions to transmission by the different stages of infection (early, late, and funeral). We found that a wide range of forecasted trajectories fit approximately equally well to the early data. By including the correction factor term, however, the best-fit models correctly forecasted EVD activity for all three countries, both individually and for all countries combined. In particular, the models correctly forecasted the slow-down and stabilization in Liberia, as well as the continued exponential growth in Sierra Leone through November 2014. Parameter unidentifiability issues hindered estimation of the relative contributions of each stage of transmission from incidence and deaths data alone, which poses a challenge in determining optimal intervention strategies, and underscores the need for additional data collection. Even with these limited data, however, it is still possible to accurately capture and predict the epidemic dynamics by using a simplified correction term that approximately accounts for the complex underlying factors driving disease spread.

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“…To address these challenges, several new models have been suggested each providing quite different results, for example [1], [2], [3], [4], [13], [14], [15]. We also note that different aspects of possible control have been intensively studied in the literature including distribution strategies for vaccination and antibiotic programs [12] as well as travel restrictions [8].…”

Section: Introductionmentioning

confidence: 99%