New Model for the COVID-19 Reported Cases and Deaths of Ghana in Accelerated Spread and Prediction of the Delayed Phase

Abstract

There is an ongoing investigation on the transmission characteristics of COVID-19 with respect to country-based inflection points, nature of distribution and prediction of future trends. In this study, a new accelerated and delayed spread models for COVID-19 reported cases and deaths in Ghana were developed. Optimization techniques coupled with interpolations, least square and non-linear regression methods, to come out with an informed modeling strategy to predict the delayed spread for the case of Ghana were adopted. Derivative and tangent methods were also applied to determine inflection points for Ghana’s cases and death from COVID-19. The data used for the study covered the first 250 days of events and interventions of the pandemic in Ghana. It was realized that the distribution of the COVID-19 situation in Ghana followed an exponential distribution curve. A modification of the developed model to help optimize the error between observed and estimated values yielded an improvement in the prediction of the delayed phase. Our derived parameters revealed that transmission of the virus between phases depended on changes in the precautionary measures and peoples' behaviors. The study thus shows that Ghana passed her inflection point of reported cases on Sunday 19th July, 2020 and may currently be in the delayed phase characterized with a staggering trend where new infections similar in magnitude to previous infections may upsurge. The correlation between reported cases and deaths revealed linear dependence with positive deviation between accelerated and delayed phases. In conclusion, the study predicted the commencement of a new wave in Ghana after Wednesday October 28, 2020 with higher intensity than what was previously observed if timely impositions of interventions to minimize the effect of the second wave are not taken.

On the Modeling of Causative and Dependence Relationship of Cancers based on Gender and Cumulative Incidence

“…Overall, the global burden of cancer incidence and death is quickly increasing, resulting in population aging and growth, and changes in the prevalence and distribution of cancer risk factors. Cancerous disease, a cause of premature death, has been weighed in terms of how it affects social and economic development levels of a nation [5][6][7][8][9].…”

Empirical Modeling of COVID-19 Evolution with High/Direct Impact on Public Health and Risk Assessment

“…The second phase of the pandemic corresponds to the accelerated growth phase and started on the 29 of February. The third phase, beginning on 19 June, corresponds to the delayed growth phase, where a time-dependent, exponentially decreasing transmission rate occurs due to major public interventions and social distancing measures [ 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 ]. Mathematical models have been proven to play a significant role in the study of infectious diseases [ 23 ].…”

“…Mathematical models have been proven to play a significant role in the study of infectious diseases [ 23 ]. They can provide deeper insight into the dynamics of the diseases’ spread and also suggest effective control strategies to help local public health authorities in the process of control and decision-making/risk management to protect populations and to end the crisis [ 24 , 25 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 ]. In the present work, as a semi-empirical study, the pandemic spread behavior will be modeled in simplified exponential form over time with three adjustable parameters in order to offer an accurate prediction and estimation, as well as to contribute to the improvement and the advancement of certain theories by proposing a particular solution to their systems by using theoretical equations.…”