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Rahman A, Othman N, Kuddus MA, Hasan MZ. Impact of the COVID-19 pandemic on child malnutrition in Selangor, Malaysia: A pilot study. J Infect Public Health 2024; 17:833-842. [PMID: 38547630 DOI: 10.1016/j.jiph.2024.02.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 02/21/2024] [Accepted: 02/29/2024] [Indexed: 04/15/2024] Open
Abstract
BACKGROUND Child malnutrition risk factors are globally recognized, but the specific impact of the COVID-19 pandemic on the prevalence of child malnutrition, considering socioeconomic burdens and changes in family lifestyles, remains underexplored. This study aims to identify the significance of COVID-19-related factors in relation to the prevalence of child malnutrition in Selangor, Malaysia. METHODS Purposive sampling was employed in this pilot study to select the households with under-5 children and, a structured questionnaire was developed to gather data. Chi-squared tests, logistic regression modelling and World Health Organisation AnthroPlus software-based visualization were used for analyses. RESULTS The present study's findings indicate that demographic and social factors, including 'Citizenship,' 'Type of House,' 'Number of Earning Members,' 'Father's Highest Educational Level,' and 'Number of Children in a Family,' have a statistically significant association with Wasting. Additionally, the mother's 'Highest Educational Level' is found to be linked to underweight prevalence. Within COVID-19 factors, "COVID-19 Impact on Employment/Business" demonstrated significance for both stunting and wasting. Multivariate analysis revealed disparities in childhood malnutrition by gender, age, and factors such as "COVID-19 impact on children's physical activity" and "COVID-19 impact on children's decrease in health over the last two weeks." CONCLUSIONS This study identified COVID-19 factors alongside sociodemographic variables with statistically significant relationships impacting childhood malnutrition in Selangor, Malaysia. The results underscored the substantial influence of the COVID-19 pandemic on child malnutrition prevalence. Decision-makers at family and community levels can benefit by considering these factors in their actions. However, the study's limitation lay in its dataset, urging larger-scale analyses to explore further sub-categories of the examined variables.
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Affiliation(s)
- Azizur Rahman
- School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, Australia.
| | - Nezza Othman
- School of Science, Monash University Malaysia, Bandar Sunway, Selangor D.E., Malaysia
| | - Md Abdul Kuddus
- School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, Australia; Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, QLD 4811, Australia; Department of Mathematics, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Md Zobaer Hasan
- School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, Australia; School of Science, Monash University Malaysia, Bandar Sunway, Selangor D.E., Malaysia
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Rahman A, Kuddus MA, Paul AK, Hasan MZ. The impact of triple doses vaccination and other interventions for controlling the outbreak of COVID-19 cases and mortality in Australia: A modelling study. Heliyon 2024; 10:e25945. [PMID: 38384567 PMCID: PMC10878934 DOI: 10.1016/j.heliyon.2024.e25945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 01/29/2024] [Accepted: 02/05/2024] [Indexed: 02/23/2024] Open
Abstract
COVID-19 is a significant public health problem around the globe, including in Australia. Despite this, Australia's Ministry of Health has expanded COVID-19 control measures widely, logistical trials exist, and the disease burden still needs more clarity. One of the best methods to comprehend the dynamics of disease transmission is by mathematical modeling of COVID-19, which also makes it possible to quantify factors in many places, including Australia. In order to understand the dynamics of COVID-19 in Australia, we examine a mathematical modeling framework for the virus in this study. Australian COVID-19 actual incidence data from January to December 2021 was used to calibrate the model. We also performed a sensitivity analysis of the model parameters and found that the COVID-19 transmission rate was the primary factor in determining the basic reproduction number (R0). Gradually influential intervention policies were established, with accurate effect and coverage regulated with the help of COVID-19 experts in Australia. We simulated data for the period from April 2022 to August 2023. To ascertain which of these outcomes is most effective in lowering the COVID-19 burden, we here assessed the COVID-19 burden (as shown by the number of incident cases and mortality) under a range of intervention scenarios. Regarding the policy of single intervention, the fastest and most efficient way to lower the incidence of COVID-19 is via increasing the first-dose immunization rate, while an improved treatment rate for the afflicted population is also helps to lower mortality in Australia. Furthermore, our results imply that integrating more therapies at the same time increases their efficacy, particularly for mortality, which significantly reduced with a moderate effort, while lowering the number of COVID-19 instances necessitates a major and ongoing commitment.
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Affiliation(s)
- Azizur Rahman
- School of Computing, Mathematics and Engineering, Charles Sturt University, NSW 2678, Australia
| | - Md Abdul Kuddus
- School of Computing, Mathematics and Engineering, Charles Sturt University, NSW 2678, Australia
- Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, QLD 4810, Australia
- Department of Mathematics, University of Rajshahi, Rajshahi-6205, Bangladesh
| | - Anip Kumar Paul
- Department of Mathematics, University of Rajshahi, Rajshahi-6205, Bangladesh
| | - Md Zobaer Hasan
- School of Computing, Mathematics and Engineering, Charles Sturt University, NSW 2678, Australia
- School of Science, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor D. E., Malaysia
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Rahman A, Kuddus MA, Ip RHL, Bewong M. Modelling COVID-19 pandemic control strategies in metropolitan and rural health districts in New South Wales, Australia. Sci Rep 2023; 13:10352. [PMID: 37365205 DOI: 10.1038/s41598-023-37240-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 06/19/2023] [Indexed: 06/28/2023] Open
Abstract
COVID-19 remains a significant public health problem in New South Wales, Australia. Although the NSW government is employing various control policies, more specific and compelling interventions are needed to control the spread of COVID-19. This paper presents a modified SEIR-X model based on a nonlinear ordinary differential equations system that considers the transmission routes from asymptomatic (Exposed) and symptomatic (Mild and Critical) individuals. The model is fitted to the corresponding cumulative number of cases in metropolitan and rural health districts of NSW reported by the Health Department and parameterised using the least-squares method. The basic reproduction number [Formula: see text], which measures the possible spread of COVID-19 in a population, is computed using the next generation operator method. Sensitivity analysis of the model parameters reveals that the transmission rate had an enormous influence on [Formula: see text], which may be an option for controlling this disease. Two time-dependent control strategies, namely preventive (it refers to effort at inhibiting the virus transmission and prevention of case development from Exposed, Mild, Critical, Non-hospitalised and Hospitalised population) and management (it refers to enhance the management of Non-hospitalised and Hospitalised individuals who are infected by COVID-19) measures, are considered to mitigate this disease's dynamics using Pontryagin's maximum principle. The most sensible control strategy is determined through the cost-effectiveness analysis for the metropolitan and rural health districts of NSW. Our findings suggest that of the single intervention strategies, enhanced preventive strategy is more cost-effective than management control strategy, as it promptly reduces COVID-19 cases in NSW. In addition, combining preventive and management interventions simultaneously is found to be the most cost-effective. Alternative policies can be implemented to control COVID-19 depending on the policymakers' decisions. Numerical simulations of the overall system are performed to demonstrate the theoretical outcomes.
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Affiliation(s)
- Azizur Rahman
- School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW, 2678, Australia.
| | - Md Abdul Kuddus
- School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW, 2678, Australia
- Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, QLD, 4811, Australia
- Department of Mathematics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Ryan H L Ip
- School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW, 2678, Australia
| | - Michael Bewong
- School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW, 2678, Australia
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Abuauf M, Raboei EH, Alshareef M, Rabie N, Al-Zailai R, Alharbi A, Felemban W, Al Nasser I, Shalabi H. Corona virus 19(COVID-19) Conceptual Modeling a Single-Center Prospective: Cross-Sectional Study. JMIR Form Res 2023. [PMID: 37256829 DOI: 10.2196/41376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023] Open
Abstract
BACKGROUND Conceptual models are abstract representations of the real world. They are used to refine medical and non-medical healthcare scopes of service. During the covid 19 pandemic numerous analytic predictive models were generated aiming to evaluate the impact of policies implemented on the mitigating of COVID-19 pandemic, the psycho-social factors that might govern general population adherence to these policies, identify factors that might affect COVID-19 vaccine uptake and allocation. The outcomes of these analytic models helped set priorities when vaccines were available, and predicted readiness to resume non-COVID-19 healthcare services. OBJECTIVE The objective of our research was to implement a descriptive-analytical conceptual model that analyzes the data of all COVID-19-positive cases admitted to our hospital 1st of March to the 31st of May 2020, the initial wave of the pandemic, the time interval during which local policies and clinical guidelines were constantly updated to mitigate the local effects of SARS-CoV-2, minimize mortality, ICU admission, and ensure the safety of healthcare providers. The primary outcome of interest was to identify factors that might affect mortality and ICU admission, and the impact of the policy implemented on SARS-CoV-2 positivity among healthcare providers. The secondary outcome of interest was to evaluate the sensitivity of the SARS-coV-2 visual score implemented by the Saudi MOH for COVID-19- risk assessment as well as CURB-65 scores in predicting ICU admission or mortality among the study population. METHODS This was a cross-sectional study. The relevant attributes were constructed based on research findings from the first wave of the pandemic and were electronically retrieved from the hospital database. Analysis of the conceptual model was based on the International Society for Pharmacoeconomics and Outcomes Research guidelines and the Society for Medical Decision-Making. RESULTS 275 were SARS-CoV-2- positive within the study design interval. The conceptualization model revealed a low-risk population based on the following attributes: the mean age was 42 ± 19.2 years, 19% of the study population were senior adults ≥ 60 years, 80% had a CURB-65 score < 4, 53% had no comorbidities, 5% had extreme obesity, and 2% had a significant hematological abnormality. The overall rate of ICU admission for the study population was 5%, with a 1.5% overall mortality. The multivariate correlation analysis revealed that high selectivity was adopted, wherein patients with complex medical problems were not sent to MOH isolation facilities. Furthermore, 5% of healthcare providers were SARS-CoV-2-positive, and none were healthcare providers allocated to the COVID-19 screening areas indicating the effectiveness of the policy implemented to ensure the safety of healthcare providers. CONCLUSIONS Based on the conceptual model outcome, the selectivity applied to retaining high-risk populations within the hospital might have contributed to the low mortality rate observed without increasing the risk to attending healthcare providers. CLINICALTRIAL Not applicable.
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Affiliation(s)
- Mawahib Abuauf
- Department of pediatric, neonatology king Fahad armed forces hospital Jeddah, Al-DUHA street (65) MISHRIFA 7, Jeddaha, SA
| | - Enaam Hassan Raboei
- king Fahad armed forces hospital Jeddah, Chairperson of the research committee, Head of pediatric Surgery Division. Consultant Pediatric Surgeon, Jeddah, SA
| | - Muneera Alshareef
- king Fahad armed forces hospital Jeddah, Consultant Endocrinologist, Member of hospital research committee, Jeddah, SA
| | - Nada Rabie
- king Fahad armed forces hospital Jeddah, Consultant Infection Disease Adults, Member of hospital research committee, Jeddah, SA
| | - Roaa Al-Zailai
- king Fahad armed forces hospital Jeddah, Consultant Pediatric Infection Disease, Jeddah, SA
| | - Abdullah Alharbi
- king Fahad armed forces hospital Jeddah, Consultant Pathologist, Jeddah, SA
| | - Walaa Felemban
- king Fahad armed forces hospital Jeddah, Consultant Pathology, Jeddah, SA
| | - Ibrahim Al Nasser
- king Fahad armed forces hospital Jeddah, Hospital director, Consultant Radiologist, Jeddah, SA
| | - Hanin Shalabi
- king Fahad armed forces hospital Jeddah, Research and Data Management Specialist, Jeddah, SA
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Magana-Arachchi DN, Wanigatunge RP, Vithanage MS. Can infectious modelling be applicable globally - lessons from COVID 19. CURRENT OPINION IN ENVIRONMENTAL SCIENCE & HEALTH 2022; 30:100399. [PMID: 36320817 PMCID: PMC9612404 DOI: 10.1016/j.coesh.2022.100399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 09/14/2022] [Accepted: 10/18/2022] [Indexed: 06/16/2023]
Abstract
Contagious diseases are needed to be monitored to prevent spreading within communities. Timely advice and predictions are necessary to overcome the consequences of those epidemics. Currently, emphasis has been placed on computer modelling to achieve the needed forecasts, the best example being the COVID-19 pandemic. Scientists used various models to determine how diverse sociodemographic factors correlated and influenced COVID-19 Global transmission and demonstrated the utility of computer models as tools in disease management. However, as modelling is done with assumptions with set rules, calculating uncertainty quantification is essential in infectious modelling when reporting the results and trustfully describing the limitations. This article summarizes the infectious disease modelling strategies, challenges, and global applicability by focusing on the COVID-19 pandemic.
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Affiliation(s)
- Dhammika N Magana-Arachchi
- Molecular Microbiology and Human Diseases Unit, National Institute of Fundamental Studies, Kandy, Sri Lanka
| | - Rasika P Wanigatunge
- Department of Plant and Molecular Biology, Faculty of Science, University of Kelaniya, Sri Lanka
| | - Meththika S Vithanage
- Ecosphere Resilience Research Centre, Faculty of Applied Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka
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