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

Tawiah, Kassim; Abdul, Iddrisu Wahab; Asosega, Killian Asampana

doi:10.1155/2021/5543977

Cited by 12 publications

(8 citation statements)

References 25 publications

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“…The better performance of ZINBR model could be due to its ability to capture over dispersion and heterogeneity in the data sets. Similar results were also found in Tawiah et al [8] where zero-inflated models performed better than classical models in modelling COVID-19 deaths in Ghana country. Further, the actual vs fitted values of all the models are depicted in Fig.…”

Section: Results Of Zero Inflated Count Regression Modelssupporting

confidence: 88%

“…Crop pest modelling is one of the major areas of count data regression modelling wherein daily or weekly counts of insects (pests), are considered as dependent variables and corresponding weather variables are considered as exogenous variables. Though the count regression data modelling approach is applied in many areas; Identifying defects in manufacturing [4], In domestic violence data [5], caries research [6], spontaneous abortion [7], modelling of death due to covid-19 in Ghana [8] and zoological data [9] but their applications are limited in insect pest modeling. Contrary to count regression modelling, the continuous linear regression model was applied in many insect pest modelling studies and as well as in agricultural data sets; weather based regression modelling of white rust disease of Indian mustard [10], regression modelling factors influencing agricultural diversification of Karnataka [11], regression modelling of biometrical characters in Sesame [12], regression analysis of growth patterns of root and shoot morphological traits in Sesame [13], weather based YSB regression model [14], modelling of YSB population under changing climatic scenarios [15].…”

Section: Introductionmentioning

confidence: 99%

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Modelling the Relationship between Weather Variables and Yellow Stem Borer Population: A Count Data Modelling Approach

Reddy¹,

Rathod²,

Kallakuri³

et al. 2022

IJECC

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Aim: This study was conducted to model the relationship between discrete dependent variable (yellow stem borer population) and continuous weather variables. Data Description: The yellow stem borer (YSB) population and standard meteorological week (SMW) wise weather variables (temperature, relative humidity, rainfall and sunshine hours) data of Warangal centre (Telangana state) generated under All India Co-Ordinated Rice Improvement Project (AICRIP) from 2013-2021 were considered for the study. The YSB population were recorded daily using light trap with an incandescent bulb and are counted as weekly cumulative catches. Methodology: The weekly cumulative trapped YSB populations and weekly averages of climatological data were considered as inputs to the models under consideration. In this study the classical linear regression i.e. step-wise multiple linear regression and count regression models such as Poisson, negative binomial, zero inflated Poisson and zero inflated negative binomial regression models were employed. Result: The empirical results revealed that the zero inflated count regression models viz., zero inflated Poisson regression and zero inflated negative binomial regression models performed better compared to the classical linear regression, Poisson and negative binomial regression models, further the negative binomial regression model outperformed all models as it yielded lowest mean square error (MSE) and highest R2 values. The average percentage reduction in accuracy of zero-inflated negative binomial regression model over classical model was around 4 percent. Conclusion: Based on the results obtained in this study, it is concluded that the zero inflated models performs better compared to classical models as they are unable to handle the presence of excess zeroes, as a result provides more prediction error and lower R2 values. Further, the models developed in this study will be of great assistance in identifying the factors influencing occurrence of YSB population in rice.

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Section: Results Of Zero Inflated Count Regression Modelssupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Modelling the Relationship between Weather Variables and Yellow Stem Borer Population: A Count Data Modelling Approach

Reddy¹,

Rathod²,

Kallakuri³

et al. 2022

IJECC

View full text Add to dashboard Cite

show abstract

“…Time-series models have been broadly applied to COVID-19 data. Tawiah et al [ 29 ] proposed zero-inflated time-series model for COVID-19 deaths in Ghana. Luo et al [ 30 ] used LSTM and XGBoost algorithms to predict COVID-19 transmission in America using time series.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Conventional Modeling Techniques with the Neural Network Autoregressive Model (NNAR): Application to COVID-19 Data

Daniyal

Tawiah

Muhammadullah

et al. 2022

Journal of Healthcare Engineering

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The coronavirus disease 2019 (COVID-19) pandemic continues to destroy human life around the world. Almost every country throughout the globe suffered from this pandemic, forcing various governments to apply different restrictions to reduce its impact. In this study, we compare different time-series models with the neural network autoregressive model (NNAR). The study used COVID-19 data in Pakistan from February 26, 2020, to February 18, 2022, as a training and testing data set for modeling. Different models were applied and estimated on the training data set, and these models were assessed on the testing data set. Based on the mean absolute scaled error (MAE) and root mean square error (RMSE) for the training and testing data sets, the NNAR model outperformed the autoregressive integrated moving average (ARIMA) model and other competing models indicating that the NNAR model is the most appropriate for forecasting. Forecasts from the NNAR model showed that the cumulative confirmed COVID-19 cases will be 1,597,180 and cumulative confirmed COVID-19 deaths will be 32,628 on April 18, 2022. We encourage the Pakistan Government to boost its immunization policy.

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“…Situations were different in Ghana because there was no clear immediate plan to address the coronavirus though the government imposed a partial lockdown on its two major cities, which was lifted shortly after citizens were mandated to use face masks in public places (Adom, 2020; Kenu et al, 2020). Health facilities and caregivers in Ghana experienced inadequate and inconsistent supply of personal protective equipment, as well as non-payment of allowances and strikes that threatened efforts to curb the outbreak of COVID-19 (Tawiah et al, 2021).…”

Section: Results/findingsmentioning

confidence: 99%

Communication Strategies in Relation to COVID-19 in South Africa and Ghana: A Systematic Review

Boateng,

Gumede

2023

Journal of Creative Communications

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COVID-19 is a novel severe acute respiratory syndrome coronavirus 2 (SAR–CoV-2) spread from person to person through infected air droplets of saliva and discharged from sneezes and coughs. This study seeks to contribute to knowledge and understanding of how coronavirus outbreaks could be addressed by examining communication and media strategies used by governments and public health institutions in South Africa and Ghana during the coronavirus pandemic. The study systematically analysed published data on COVID-19 in South Africa and Ghana from 2019 to 2020 to identify recurring themes to discuss issues regarding communication strategies in response to the outbreak. This study found various inadequacies and challenges to communication and media strategies to address the spread of COVID-19. The governments and public health institutions in South Africa and Ghana used multiple mass media channels to communicate different messages and create awareness about COVID-19. This article recommends the improvement of communication and media engagements between governments and health stakeholders in South Africa and Ghana to increase public awareness of the risks, threats and outcomes of COVID-19. The media in South Africa and Ghana must conduct fact finding of information about coronavirus from official sources in government and health institutions before dissemination to the public to minimise fake news, misinformation and disinformation. The governments and health institutions must not rely solely on traditional mass media strategies but also integrate indigenous communication strategies for engagements to address the challenges of mass media to increase public awareness about COVID-19 in South Africa and Ghana.

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

Cited by 12 publications

References 25 publications

Modelling the Relationship between Weather Variables and Yellow Stem Borer Population: A Count Data Modelling Approach

Modelling the Relationship between Weather Variables and Yellow Stem Borer Population: A Count Data Modelling Approach

Comparison of Conventional Modeling Techniques with the Neural Network Autoregressive Model (NNAR): Application to COVID-19 Data

Communication Strategies in Relation to COVID-19 in South Africa and Ghana: A Systematic Review

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