Cost-effective modelling of the transmission dynamics of malaria: a case study in Bangladesh

Azizur Rahman, Abdul Kuddus

Research output: Contribution to journalArticle

Abstract

Each year infectious disease such as malaria causes severe population loss in both the developing and developed countries. Modelling of malaria is considered one of the effective ways to understand and mitigate this problem. This paper develops a reliable quantitative modelling technique to support the design and characterization of the malaria disease in Bangladesh. Results reveal that the effects of some influencing factors such as service factors (i.e. lack of budgets in government agencies, antiviral medicine and poor quality of service facilities), disease related factors (i.e. nutrition status and existing illness), environmental factors (i.e. urbanization and crowdedness) and sociological factors (i.e. education and religious believes) are significant. In particular, social factor education showed significant multidimensional impacts to the occurrence of the disease and its mitigation. A poor educational status leads to a range of impacts through –i) lack of awareness in the causes of malaria, severity of health effect and how and where to access the treatment services, ii) refusal of vaccination, and iii) unfamiliarity with good health and nutritional facts contributing to nutrition status. The study also provides the prediction of new cases in malaria until 2025 using the developed model and recommends, control strategies of malaria.
Original languageEnglish
Pages (from-to)1-24
Number of pages24
JournalCommunications in Statistics: Case Studies, Data Analysis and Applications
Publication statusAccepted/In press - 2020

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Bangladesh
Malaria
Costs and Cost Analysis
Nutritional Status
Environmental Illness
Government Agencies
Education
Educational Status
Urbanization
Health
Budgets
Developed Countries
Developing Countries
Antiviral Agents
Communicable Diseases
Medicine
Population

Cite this

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abstract = "Each year infectious disease such as malaria causes severe population loss in both the developing and developed countries. Modelling of malaria is considered one of the effective ways to understand and mitigate this problem. This paper develops a reliable quantitative modelling technique to support the design and characterization of the malaria disease in Bangladesh. Results reveal that the effects of some influencing factors such as service factors (i.e. lack of budgets in government agencies, antiviral medicine and poor quality of service facilities), disease related factors (i.e. nutrition status and existing illness), environmental factors (i.e. urbanization and crowdedness) and sociological factors (i.e. education and religious believes) are significant. In particular, social factor education showed significant multidimensional impacts to the occurrence of the disease and its mitigation. A poor educational status leads to a range of impacts through –i) lack of awareness in the causes of malaria, severity of health effect and how and where to access the treatment services, ii) refusal of vaccination, and iii) unfamiliarity with good health and nutritional facts contributing to nutrition status. The study also provides the prediction of new cases in malaria until 2025 using the developed model and recommends, control strategies of malaria.",
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AB - Each year infectious disease such as malaria causes severe population loss in both the developing and developed countries. Modelling of malaria is considered one of the effective ways to understand and mitigate this problem. This paper develops a reliable quantitative modelling technique to support the design and characterization of the malaria disease in Bangladesh. Results reveal that the effects of some influencing factors such as service factors (i.e. lack of budgets in government agencies, antiviral medicine and poor quality of service facilities), disease related factors (i.e. nutrition status and existing illness), environmental factors (i.e. urbanization and crowdedness) and sociological factors (i.e. education and religious believes) are significant. In particular, social factor education showed significant multidimensional impacts to the occurrence of the disease and its mitigation. A poor educational status leads to a range of impacts through –i) lack of awareness in the causes of malaria, severity of health effect and how and where to access the treatment services, ii) refusal of vaccination, and iii) unfamiliarity with good health and nutritional facts contributing to nutrition status. The study also provides the prediction of new cases in malaria until 2025 using the developed model and recommends, control strategies of malaria.

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