Mathematical modeling of COVID-19 infection dynamics in Ghana: Impact evaluation of integrated government and individual level interventions

Dwomoh, Duah; Iddi, Samuel; Adu, Bright; Aheto, Justice Moses K.; Sedzro, Kojo Mensah; Bosomprah, Samuel

doi:10.1016/j.idm.2021.01.008

Cited by 24 publications

(13 citation statements)

References 29 publications

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“…Throughout, we focus our analyses on empirically supported parameter values including realistic testing rates. While many existing COVID-19 SIR-like compartmental models explore the effects of testing with forms of isolation like quarantine or hospitalization, the majority of these studies assume simple linear equations for the rates at which tests are administered and individuals are isolated Adhikari et al, 2021 , Ahmed et al, 2021 , Amaku et al, 2021 , Choi and Shim, 2021 , Dwomoh et al, 2021 , Hussain et al, 2021 , Ngonghala et al, 2020 , Rong et al, 2020 , Saldaña et al, 2020 , Sturniolo et al, 2021 , Tuite et al, 2020 , Verma et al, 2020 , Youssef et al, 2021 . We show (see [testingmodel]Methods: Testing model) that linear models can not fully describe highly limited testing capacity scenarios, and we propose a novel testing model which flexible accounts for resource-rich and resource-limited settings.…”

Section: Introductionmentioning

confidence: 99%

How optimal allocation of limited testing capacity changes epidemic dynamics

Calabrese

Demers

2022

Journal of Theoretical Biology

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Insufficient testing capacity has been a critical bottleneck in the worldwide fight against COVID-19. Optimizing the deployment of limited testing resources has therefore emerged as a keystone problem in pandemic response planning. Here, we use a modified SEIR model to optimize testing strategies under a constraint of limited testing capacity. We define pre-symptomatic, asymptomatic, and symptomatic infected classes, and assume that positively tested individuals are immediately moved into quarantine. We further define two types of testing. Clinical testing focuses only on the symptomatic class. Non-clinical testing detects pre- and asymptomatic individuals from the general population, and a concentration parameter governs the degree to which such testing can be focused on high infection risk individuals. We then solve for the optimal mix of clinical and non-clinical testing as a function of both testing capacity and the concentration parameter. We find that purely clinical testing is optimal at very low testing capacities, supporting early guidance to ration tests for the sickest patients. Additionally, we find that a mix of clinical and non-clinical testing becomes optimal as testing capacity increases. At high but empirically observed testing capacities, a mix of clinical testing and non-clinical testing, even if extremely unfocused, becomes optimal. We further highlight the advantages of early implementation of testing programs, and of combining optimized testing with contact reduction interventions such as lockdowns, social distancing, and masking.

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Section: Introductionmentioning

confidence: 99%

How optimal allocation of limited testing capacity changes epidemic dynamics

Calabrese

Demers

2022

Journal of Theoretical Biology

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“…Dwomoh et al [ 8 ] used mathematical models to investigate COVID-19 infection dynamics in Ghana and delivered a brief forecast of the pandemic trajectory in the country using generalized growth models. They investigated the effective basic reproduction number of the virus in real time applying different techniques of estimation, thereby predicting worse case scenarios amidst integrated individual and Government interventions by the use of compartmental models.…”

Section: Introductionmentioning

confidence: 99%

Zero-Inflated Time Series Modelling of COVID-19 Deaths in Ghana

Tawiah

Abdul

Asosega

2021

Journal of Environmental and Public Health

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Discrete count time series data with an excessive number of zeros have warranted the development of zero-inflated time series models to incorporate the inflation of zeros and the overdispersion that comes with it. In this paper, we investigated the characteristics of the trend of daily count of COVID-19 deaths in Ghana using zero-inflated models. We envisaged that the trend of COVID-19 deaths per day in Ghana portrays a general increase from the onset of the pandemic in the country to about day 160 after which there is a general decrease onward. We fitted a zero-inflated Poisson autoregressive model and zero-inflated negative binomial autoregressive model to the data in the partial-likelihood framework. The zero-inflated negative binomial autoregressive model outperformed the zero-inflated Poisson autoregressive model. On the other hand, the dynamic zero-inflated Poisson autoregressive model performed better than the dynamic negative binomial autoregressive model. The predicted new death based on the zero-inflated negative binomial autoregressive model indicated that Ghana’s COVID-19 death per day will rise sharply few days after 30th November 2020 and drastically fall just as in the observed data.

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“…The estimates also differ slightly from Dwomoh and colleagues (2021), but may be explained by the differences in the methods including the fact that these authors used data from the first 60 days. 14 Nevertheless, Rt remained greater than 1 at the national level and in most regions indicating sustained transmission. It is therefore imperative that public health measures are strengthened throughout the country and efforts are prioritized especially in regions with larger population sizes as the disparity in the case burden across regions was reported in multiple studies.…”

mentioning

confidence: 94%

Transmission dynamics of COVID-19 in Ghana and the impact of public health interventions

Ofori

Schwind

Sullivan

et al. 2021

Preprint

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The study characterized the transmission of COVID-19 in Ghana by estimating the time-varying reproduction number (Rt) and exploring the effect of various public health interventions at the national and regional levels. The median Rt for Ghana and six out of sixteen regions dropped from greater than 1 in March 2020 to less than 1 in September but increased above 1 in January 2021. The relaxation of movement restrictions and religious gatherings were not associated with increased Rt in the regions with lower case burdens. However, Rt increased in most regions after schools were reopened in January 2021. In a regression analysis, we estimated that the per-capita cumulative case count increased with population size. Findings indicated the public health interventions reduced the Rt at the national level while at the regional levels, the Rt fluctuated, and the extent of fluctuation varied across regions.

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Mathematical modeling of COVID-19 infection dynamics in Ghana: Impact evaluation of integrated government and individual level interventions

Cited by 24 publications

References 29 publications

How optimal allocation of limited testing capacity changes epidemic dynamics

How optimal allocation of limited testing capacity changes epidemic dynamics

Zero-Inflated Time Series Modelling of COVID-19 Deaths in Ghana

Transmission dynamics of COVID-19 in Ghana and the impact of public health interventions

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