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Socioeconomic Determinants of Malaria Prevention Options Adoption of Households in the North West Region of Cameroon

Received: 19 May 2020    Accepted: 1 June 2020    Published: 23 July 2020
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Abstract

Despite its simple and perceived affordable prevention methods, malaria has over time remained the main killer disease in Africa, Sub Sahara Africa, Cameroon and the North West Region in Particular. It is from the above backdrop that this study uses quantitative approach to examine the socioeconomic determinants of malaria prevention options adoption by households in the North West Region of Cameroon. Thus, data was collected from 400 households purposively selected among the top ten health districts with high prevalence of malaria in the North West Region of Cameroon. The study used both Ordinary Least Square, Poisson and Ordered Logit Regression techniques to capture the socioeconomic determinants of malaria prevention behaviour of households. These different methodologies were used to check the robustness of the results as methodology changes. The findings reveal that community based malaria prevalence, knowledge of malaria signs, knowledge of malaria cause, age of household heads, marital status of household heads, household size, cost of malaria prevention, household monthly income, education and employment status of the household head are all socioeconomic factors that determine malaria prevention options adopted by households in the North West Region. Based on the findings, the study strongly recommends further sensitization campaigns; creation of community-based malaria control committees; sponsored media programs; household empowerment programs, free distribution of Insecticide Treated Bed Nets, the use of holistic rather than individualistic malaria prevention strategies, among others as specific policy measures that can health achieve the much desired goal of eradicating malaria in the North West Region and Cameroon as a whole.

Published in International Journal of Health Economics and Policy (Volume 5, Issue 2)
DOI 10.11648/j.hep.20200502.11
Page(s) 15-30
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Malaria Prevention Behaviour, Socioeconomic Determinants, Ordinary Least Square, Poisson, Ordered Logit, North West Region, Cameroon

References
[1] Packard, R. (2008). The Making of a Tropical Disease: A Short History of Malaria. Johns Hopkins University Press.
[2] Devarajan, B. C., & Gersbach, S. H. (2006). The long-run economic costs of AIDS: a model and an application to South Africa. World Bank Economic Review, 20, 55–89.
[3] Gallup, J. L., & Sachs, J. D. (2001). The economic burden of malaria. American Journal of Tropical Medicine & Hygiene, 64 (supp 1), 85-96.
[4] Artadi, E., & Sala-I-Martin, X. (2003). The economic tragedy of the XXth Century: Growth in Africa. NBER Working Paper 9865. National Bureau of Economic Research. Massachusetts, USA: Cambridge.
[5] Ngum, J. W., Ongolo-Zogo, P., Tallah, E., Leke, R., & Mbacham, W. (2010). Policy Brief on scaling up malaria control interventions in Cameroon. Executive summary.
[6] Kouznetsov, R. L. (1977). Malaria control by application of indoor spraying of residual insecticides in tropical Africa and its impact on community health. Tropical doctor, 7 (2), 81-91.
[7] Mbenda, H. G. N., Awasthi, G., Singh, P. K., Gouado, I., & Das, A. (2014). Does malaria epidemiology project Cameroon as ‘Africa in miniature’?. Journal of biosciences, 39 (4), 727-738.
[8] Ministry of Public Heaalth (MoH), (2007). National Malaria Control Programme, NMCP 2007-2010. Yaounde, Cameroon.
[9] Ongolo-Zogo, P., & Bonono, R. C. (2010). Policy brief on improving access to artemisinin-based combination therapies for malaria in Cameroon. International Journal of Technology Assessment in Health Care, 26 (2), 237-241.
[10] Ministry of Public Heaalth (MoH), (2015). National Strategic Plan (NSP) for malaria control for 2014-2018. Yaounde, Cameroon: Cameroon Government, Ministry of Public Health.
[11] USAID. (2017). President's Malaria Initiative Cameroon Malaria Operational Plan FY 2017. USA: Center for Disease Control Prevention.
[12] Tchekountouo, O. & Col. (2016). Rapport annuel des activités de lutte contre le paludisme dans le Nord-Ouest. Bamenda: Regional Malaria Control Unit, North West Regional Delegation of Public Health.
[13] Nfor, O. N, Njimanted G. F, Yakum I. M, Fozoh I. A. (2019) Malaria Preventive Behaviour among Rural Households in the North West Region of Cameroon. J Trop Dis 7: 312. doi: 10.4172/2329-891X.1000312.
[14] Killeen, G. F., Mackenzie, F. E., Foy, B. D., Schiestelin, C., Billingsley, P., & Beier, J. C. (2000). A simplified model for predicting malaria entomologic inoculation rates based on entomologic and parasitologic parameters relevant to control. Am. J. Prop. Med Hyg, 535-544.
[15] Arrow, K. J., Panosian, C. B., & Gelband, H. (2004). Saving lives, buying time: Economics of malaria drugs in an age of resistance. Washington, DC: The national academies press.
[16] Manana, S. (2016). Public health challenges facing malaria elimination in developing countries: a review of expert opinions.
[17] Sotiroff-Junker. (1978). A Bibliography on the Behavioural, Social and Economic Aspects of Malaria and Its Control. WHO publication.
[18] Worrall, E., Basu, S., & Hanson, K. ( 2002). The relationship between socio-economic status and malaria: a review of the literature. London: Ensuring that malaria control interventions reach the poor.
[19] Heggenhougen, H. K., Hackethal, V., & Vivek, P. (2003). The behavioural and social aspects of malaria and its control: An introduction and annotated bibliography. Social, Economic and Behavioural (SEB) Research.
[20] Worrall, E., Basu, S., & Hanson, K. (2005). Is malaria a disease of poverty? A review of the literature. Tropical medicine & international health: TM & IH, 10 (10), 1047-1059.
[21] Ricci, F. (2012). Social Implications of Malaria and their Relations with Poverty. Mediterranean Journal Of Hematology And Infectious Diseases, 2035-3006.
[22] Diiro, G. M., Affognon, H. D., Muriithi, B. W., & Wanja, S. K. (2016). The Role of Gender on Malaria Preventive Behaviour among Rural Households in Kenya. Malaria Journal.
[23] Goodman, C., Hanson, K., Mills, A., Wiseman, V., & Worrall, E. (2003). The Economics Of Malaria And Its Control. Paper for the WHO/TDR Scientific Working Group on Malaria.
[24] Dako-Gyeke, M., & Kofie, H. M. (2015). Factors Influencing Prevention and Control of Malaria among Pregnant Women Resident in Urban Slums, Southern Ghana. African Journal of Reproductive Health.
[25] Choonara, S., Odimegwu, C. O., & Elwange, B. C. (2015). Factors influencing the usage of different types of malaria prevention. African Health Sciences, 15 (2).
[26] Derjew, E. T. (2017). Knowledge of Malaria Infection and Treatment-Seeking Behavior Among Tanzanian Pregnant Women. Epidemiology Commons.
[27] Tobin West, C. I., & Kanu, E. N. (2016). Factors Influencing the Use of Malaria Prevention Methods Among Women of Reproductive Age in Peri urban Communities of Port Harcourt City, Nigeria. Nigerian Postgraduate Medical Journal.
[28] Mbako, J. D., Barffo, D., Nuotol, R. K., & Alebsehehy, R. (2017). Enhancing Malaria Prevention in Cameroon Through Community Participation: An in-Depth Review. Central African Journal of Public Health, 3 (6), 97-109.
[29] Inhorn, M. C., & Brown, P. J. (1990). The anthropology of infectious disease. Annual review of Anthropology, 19 (1), 89-117.
[30] MacCormack, C. P. (1984). Human ecology and behaviour in malaria control in tropical Africa. Bulletin of the World Health Organization, 62 (Suppl), 81.
[31] Link, B. G., & Phelan, J. (1995). Social conditions as fundamental causes of disease. Journal of health and social behavior, 80-94.
[32] Farmer, K. C. (1999). Methods for measuring and monitoring medication regimen adherence in clinical trials and clinical practice. Clinical therapeutics, 21 (6), 1074-1090.
[33] Paul, B. D. (1955). Health, culture, and community. Russell Sage Foundation.
[34] Polgar, S. (1962). Health and human behavior: areas of interest common to the social and medical sciences. Current Anthropology, 3 (2), 159-205.
[35] Etkin, D. A. (1991). Break-up in Hudson Bay: its sensitivity to air temperatures and implications for climate warming. Climatological Bulletin, 25 (1), 21-34.
[36] Onwujekwe, O., Uzochukwu, B., Eze, S., Obikeze, E., Okoli, C., & Ochonma, O. (2008). Improving equity in malaria treatment: relationship of socio-economic status with health seeking as well as with perceptions of ease of using the services of different providers for the treatment of malaria in Nigeria. Malaria Journal, 7 (1), 5.
[37] Owumi, B., & Raji, S. O. (2013). Socio-cultural determinants of maternal health care seeking behaviour in seme side of Benin Republic.
[38] WHO. (2015). World malaria report. Geneva: Available online accessed from: http://apps.who.int/iris/bitstram/10665/200028/1/9789241565158_eng.pdf.
[39] Cochran, W. G. (1963). Sampling Techniques,. (2. Éd.) New York: John Wiley and Sons, Inc.
[40] Njimanted, G. F., Nfor, O. N., Yakum, I. M., & Mobit, M. O. (2017). Households’ Choices of Healthcare Services in the North West Region of Cameroon. Journal Of The Cameroon Academy Of Sciences, Vol. 14 No. 1, 41-55. doi: https://dx.doi.org/10.4314/jcas.v14i1.4
[41] Sahn, D. E., Younger, S. D., & Genicot, G. (2003). The Demand for Health Care Services in Rural Tanzania. Oxford Bulletin of Economics and Statistics, 65 (2), 0305-9049.
[42] Gertler, P., & Van der Gaag, J. (1990). Willingness to Pay for Medical Care: Evidence from Two Developing Countries. Baltimore, Maryland: Johns Hopkins University Press.
[43] Solís, D., Bravo-Ureta, B. E., & Quiroga, R. E. (2007). Soil conservation and technical efficiency among hillside farmers in Central America: a switching regression model. Aust J Agric Resour Econ, 491–510.
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    Ivan Mboambogoh Yakum, Godfrey Forgha Njimanted, Andrew Wujung Vukenkeng, Omarine Nlinwe Nfor. (2020). Socioeconomic Determinants of Malaria Prevention Options Adoption of Households in the North West Region of Cameroon. International Journal of Health Economics and Policy, 5(2), 15-30. https://doi.org/10.11648/j.hep.20200502.11

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    ACS Style

    Ivan Mboambogoh Yakum; Godfrey Forgha Njimanted; Andrew Wujung Vukenkeng; Omarine Nlinwe Nfor. Socioeconomic Determinants of Malaria Prevention Options Adoption of Households in the North West Region of Cameroon. Int. J. Health Econ. Policy 2020, 5(2), 15-30. doi: 10.11648/j.hep.20200502.11

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    AMA Style

    Ivan Mboambogoh Yakum, Godfrey Forgha Njimanted, Andrew Wujung Vukenkeng, Omarine Nlinwe Nfor. Socioeconomic Determinants of Malaria Prevention Options Adoption of Households in the North West Region of Cameroon. Int J Health Econ Policy. 2020;5(2):15-30. doi: 10.11648/j.hep.20200502.11

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  • @article{10.11648/j.hep.20200502.11,
      author = {Ivan Mboambogoh Yakum and Godfrey Forgha Njimanted and Andrew Wujung Vukenkeng and Omarine Nlinwe Nfor},
      title = {Socioeconomic Determinants of Malaria Prevention Options Adoption of Households in the North West Region of Cameroon},
      journal = {International Journal of Health Economics and Policy},
      volume = {5},
      number = {2},
      pages = {15-30},
      doi = {10.11648/j.hep.20200502.11},
      url = {https://doi.org/10.11648/j.hep.20200502.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.hep.20200502.11},
      abstract = {Despite its simple and perceived affordable prevention methods, malaria has over time remained the main killer disease in Africa, Sub Sahara Africa, Cameroon and the North West Region in Particular. It is from the above backdrop that this study uses quantitative approach to examine the socioeconomic determinants of malaria prevention options adoption by households in the North West Region of Cameroon. Thus, data was collected from 400 households purposively selected among the top ten health districts with high prevalence of malaria in the North West Region of Cameroon. The study used both Ordinary Least Square, Poisson and Ordered Logit Regression techniques to capture the socioeconomic determinants of malaria prevention behaviour of households. These different methodologies were used to check the robustness of the results as methodology changes. The findings reveal that community based malaria prevalence, knowledge of malaria signs, knowledge of malaria cause, age of household heads, marital status of household heads, household size, cost of malaria prevention, household monthly income, education and employment status of the household head are all socioeconomic factors that determine malaria prevention options adopted by households in the North West Region. Based on the findings, the study strongly recommends further sensitization campaigns; creation of community-based malaria control committees; sponsored media programs; household empowerment programs, free distribution of Insecticide Treated Bed Nets, the use of holistic rather than individualistic malaria prevention strategies, among others as specific policy measures that can health achieve the much desired goal of eradicating malaria in the North West Region and Cameroon as a whole.},
     year = {2020}
    }
    

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  • TY  - JOUR
    T1  - Socioeconomic Determinants of Malaria Prevention Options Adoption of Households in the North West Region of Cameroon
    AU  - Ivan Mboambogoh Yakum
    AU  - Godfrey Forgha Njimanted
    AU  - Andrew Wujung Vukenkeng
    AU  - Omarine Nlinwe Nfor
    Y1  - 2020/07/23
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    N1  - https://doi.org/10.11648/j.hep.20200502.11
    DO  - 10.11648/j.hep.20200502.11
    T2  - International Journal of Health Economics and Policy
    JF  - International Journal of Health Economics and Policy
    JO  - International Journal of Health Economics and Policy
    SP  - 15
    EP  - 30
    PB  - Science Publishing Group
    SN  - 2578-9309
    UR  - https://doi.org/10.11648/j.hep.20200502.11
    AB  - Despite its simple and perceived affordable prevention methods, malaria has over time remained the main killer disease in Africa, Sub Sahara Africa, Cameroon and the North West Region in Particular. It is from the above backdrop that this study uses quantitative approach to examine the socioeconomic determinants of malaria prevention options adoption by households in the North West Region of Cameroon. Thus, data was collected from 400 households purposively selected among the top ten health districts with high prevalence of malaria in the North West Region of Cameroon. The study used both Ordinary Least Square, Poisson and Ordered Logit Regression techniques to capture the socioeconomic determinants of malaria prevention behaviour of households. These different methodologies were used to check the robustness of the results as methodology changes. The findings reveal that community based malaria prevalence, knowledge of malaria signs, knowledge of malaria cause, age of household heads, marital status of household heads, household size, cost of malaria prevention, household monthly income, education and employment status of the household head are all socioeconomic factors that determine malaria prevention options adopted by households in the North West Region. Based on the findings, the study strongly recommends further sensitization campaigns; creation of community-based malaria control committees; sponsored media programs; household empowerment programs, free distribution of Insecticide Treated Bed Nets, the use of holistic rather than individualistic malaria prevention strategies, among others as specific policy measures that can health achieve the much desired goal of eradicating malaria in the North West Region and Cameroon as a whole.
    VL  - 5
    IS  - 2
    ER  - 

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Author Information
  • Faculty of Economics and Management Sciences, The University of Bamenda, Bambili, Cameroon; Higher Institute of Commerce and Management, The University of Bamenda, Bambili, Cameroon

  • Faculty of Economics and Management Sciences, The University of Bamenda, Bambili, Cameroon; Higher Institute of Commerce and Management, The University of Bamenda, Bambili, Cameroon

  • Faculty of Economics and Management Sciences, The University of Bamenda, Bambili, Cameroon; Higher Institute of Commerce and Management, The University of Bamenda, Bambili, Cameroon

  • Faculty of Health Sciences, The University of Bamenda, Bambili, Cameroon

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