×

zbMATH — the first resource for mathematics

Socio-economic determinants of HIV/AIDS pandemic and nations efficiencies. (English) Zbl 1140.62355
Summary: This paper examines the influence and direction of social and economic determinants of the HIV/AIDS global epidemic across nations and assesses each country’s efficiency in battling the pandemic. The initial dataset consisted of 151 countries with five dependent variables and 90 explanatory variables (reduced to 50 after extensive exploratory data analysis of missing value patterns, undesirable multi-colinearities and multivariate outliers).
Five measures were analyzed, namely HIV/AIDS Cases per 100,000 population; number and percentage of adults age 15–49 living with HIV/AIDS virus; estimated number of AIDS-related deaths for adults and children; and percentage of male sexual transmitted disease patients diagnosed with HIV/AIDS (identified by canonical correlation as not amenable to significant predictions).
Reasonably good fit regression models were developed with all coefficients significant (\(p < 10\%\)) that could explain each of the four specific AIDS measures and assess the validity of nine literature-based hypothesis.
The major conclusion of this research is that countries with lower population density that manage to provide better health system performance, per capita support (doctors, nurses and hospital beds) with better media information (radio, phone and TV access), and not necessarily higher GNP, are more likely to exhibit lower HIV/AIDS indicators. Interestingly, the “spoilers” of the widely anticipated negative relationship between HIV/AIDS prevalence and wealth of countries are the healthier of the wealthiest and the wealthier of the sickest.
The results lead to the development of a data envelopment analysis (DEA) output-oriented assurance-region model for 116 countries, with few missing data values imputed, using as inputs and outputs pertinent ratios, which identified 17 efficient nations. A list of DEA efficiencies portrays each country’s potential relatively to its peers to fight the pandemic by minimizing HIV/AIDS rates if additional resources were available.
These findings should be useful to health policy makers and researchers of multi-country studies on determinants of the AIDS pandemic and global efficient strategies for combating it.

MSC:
62P25 Applications of statistics to social sciences
62P10 Applications of statistics to biology and medical sciences; meta analysis
PDF BibTeX XML Cite
Full Text: DOI
References:
[1] Ainsworth, M.; Over, M., The economic impact of AIDS: shocks, responses and outcomes, (1992), The World Bank, Africa Technical Department Population, Health and Nutrition Division Washington, DC
[2] Altman, LK., 2000. UN warning AIDS imperils Africa’s youth. The New York Times, June 28.
[3] Anderson, R.M.; Ng, T.W.; Boily, M.C.; May, R.M., The influence of sexual-contact patterns between age classes on the predicted demographics impact of AIDS in developing countries, Annals of the New York Academy of sciences, 569, 1, 240-274, (1989)
[4] Anderson, R.M.; Gupta, S.; Ng, W., The significance of sexual partner contact networks for the transmission dynamics of HIV, Journal of acquired immune deficit syndromes, 3, 4, 417-429, (1990)
[5] Archavanitkul, K.; Guest, P., Migration and the commercial sex sector in Thailand, Health transition review, 4, 273-295, (1994)
[6] Barnett, T.; Whiteside, A.; Khodakevich, L.; Kruglov, Y.; Steshenka, V., The HIV/AIDS epidemic in ukraine: its potential social and economic impact, Social science and medicine, 51, 1387-1403, (2000)
[7] Berry, D.E., The emerging epidemiology of rural AIDS, Journal of rural health, 9, 4, 293-304, (1993)
[8] Breuer, N., AIDS threatens global business. Workforce. 2000. Available from: <www.workforce.com>.
[9] Brunswick, A.F.; Flory, M.J., Changing HIV infection rates and risk in an african – american community cohort, AIDS care, 10, 3, 267-281, (1998)
[10] Centers for Disease Control, Global AIDS program report: the global HIV and AIDS epidemic, Journal of the American medical association, 285, 24, 434-439, (2001)
[11] Clavel, F., Guetard, D., Brun-Vezinet, F., et al., 1986. Isolation of a new human retrovirus from West African patients with AIDS. Science 18; 233(4761), 343-346.
[12] Cohn, S.E.; Klein, J.D.; Mohr, J.E.; Van der Horst, C.M.; Weber, D.J., The geography of AIDS: patterns of urban and rural migration, South medical journal, 87, 6, 599-606, (1994)
[13] Cooper, W.W.; Seiford, L.M.; Tone, K., Data envelopment analysis, (2000), Kluwer Academic Publishers Dordrecht, Netherlands
[14] De Cock, K.; Weiss, H.A., The global epidemiology of HIV/AIDS, Tropical medicine and international health, 5, 7, A3-A9, (2000)
[15] Dempster, A.P.; Laird, N.M.; Rubin, D.B., Maximum likelihood from incomplete data via the EM algorithm, Journal of the royal statistical society, 39, 1, 1-38, (1977) · Zbl 0364.62022
[16] Edwards, J., Al-Hmoud, R.B., 2003. AIDS mortality and economic growth: A cross-country analysis using income-stratified data. Available from: <http://www3.tltc.ttu.edu/ecowp/working%20paper/w2003_01.pdf>.
[17] ()
[18] Folkers, G.K.; Faucci, A.S., The AIDS research model: implications for other infectious diseases of global health importance, Journal of the American medical association, 286, 4, 458-461, (2001)
[19] Fortune, October 27, 2003, pp. S1-S6.
[20] Friedman, S.R., HIV-related politics in long-term perspective, AIDS care, 10, 2, S93-S103, (1998)
[21] Guillies, P.; Tolley, K.; Wolstenholme, J., Is AIDS a disease of poverty, AIDS care, 8, 3, 351-363, (1996)
[22] Hair, J.F.; Anderson, R.E.; Tatham, R.L.; Black, W.C., Multivariate data analysis, (1998), Prentice Hall River, NJ
[23] Jochelson, K.; Mothibeli, M.; Leger, J.P., HIV and the immigrant labor in south africa, International journal of health services, 21, 157-173, (1991)
[24] Johnson, D., Applied multivariate methods to data analysis, (1998), Duxbury Press Pacific Grove, CA
[25] Joint United Nations Program on HIV/AIDS and World Health Organization, 2000. AIDS Epidemic Update: December 2000. UNAIDS/WHO. Geneva, Switzerland.
[26] Joint United Nations Program on HIV/AIDS and World Health Organization, 2001. AIDS Epidemic Update: December 2001. UNAIDS/WHO. Geneva, Switzerland.
[27] Little, J.A., Regression with missing X’s: A review, Journal of the American statistical association, 87, 1227-1237, (1992)
[28] Meekers, D., Van Rossem, R., Silva, M., Koleros, A., 2003. The reach and impact of radio communication campaigns on reproductive health in Malawi. Available from: <http://www.cpc.unc.edu/measure/publications/pdf/wp-04-83.pdf#search=’radio%20aids%20campaigns>.
[29] Mertens, T.E.; Low-Beer, D., HIV and AIDS: where is the epidemic going?, Bulletin of world health organisation, 74, 2, 121-129, (1996)
[30] Mesquita, F.; Doneda, D.; Gandolfi, D.; Nemes, M.I.; Andrade, T.; Bueno, R.; Piconez e Trigueiros, D., Brazilian response to the human immunodeficiency virus/acquired immunodeficiency syndrome epidemic among injection drug users, Clinical infection diseases, 15, 37 Suppl 5, S382-S385, (2003)
[31] Naik, G., HIV’s impact is seen by UN as even worse, Wall street journal, February 27, (2003)
[32] Nakashima, A.K.; Horsley, R.; Frey, R.L.; Sweeney, P.A.; Weber, J.T.; Fleming, P.L., Effect of HIV reporting by name on use of HIV testing in publicly funded counseling and testing programs, Journal of the American medical association, 2, 16, 1421-1426, (1998)
[33] OneWorld Radio AIDS Network, 2002. Available from: <http://www.dgroups.org/groups/AIDSRadio/index.cfm?op=dsp_showmsg&listname=AIDSRadio&msgid=49746&cat_id=955>.
[34] Orubuloye, I.O.; Caldwell, P.; Caldwell, J.C., The role of high risk occupation in the spread of AIDS: truck drivers and itinerant market women in nigeria, International family planning perspectives, 2, 43-48, (1993)
[35] Parker, R., The global HIV/AIDS pandemic, structural inequalities, and the politics of international health, American journal of public health, 92, 3, 343-346, (2002)
[36] Peters, R.; Sikorski, R., The AIDS net: HIV/AIDS resources on the world wide web, Journal of the American medical association, 280, 23, 2037-2038, (1998)
[37] Piot, P.; Aggleton, P., The global epidemic, AIDS care, 10, 2, S201-S208, (1998)
[38] Piot, P.; Bartos, M.; Ghys, P.; Walker, N.; Schwartländer, B., The global impact of HIV/AIDS, Nature, 410, 968-973, (2001)
[39] Pradinaud, R.; Sainte-Marie, D.; Girardeau, I.; Cassiede, P., Infection by the human immunodeficiency virus (HIV) in French guyana. dermato-venereologic problems, La medicina tropical, 49, 1, 21-28, (1989)
[40] Quinn, T., Global burden of the HIV pandemic, Lancet, 348, 99-106, (1996)
[41] Ravindra, K.; Naik, D.N., Applied multivariate statistics with SAS software, (1999), John Wiley & Sons
[42] Romo, L.F.; Berenson, A.B.; Segars, A., Sociocultural and religious influences on the normative contraceptive practices in latino women in the unites states, Contraception, 69, 219-225, (2004)
[43] Sambamoororthi, Usha; McAlpine, Donna D., Racial, ethnic socioeconomic and access disparities in the use of preventive services among women, Preventive medicine, 37, 475-484, (2003)
[44] Setel, P., The effects of HIV and AIDS on fertility in east and central africa, Health transition review, 5, Suppl., 179-189, (1995)
[45] Solomon, S.; Chakraborty, A.; Yepthomi, R.D., A review of the HIV epidemic in India, AIDS education prevention, 16, 3 Suppl A, 155-169, (2004)
[46] Thanassoulis, P., Introduction to the theory and application of data envelopment analysis, (2001), Kluwer Academic Publishers Dordrecht, Netherlands
[47] The Futurist, AIDS in developing nations, 28, 6, 57-58, (1994)
[48] Voelker, R., Setting priorities and budgets to fight against global AIDS, Journal of the American medical association, 284, 21, 2709-2710, (2000)
[49] Wall Street Journal, 2001. Twenty years of AIDS in America. May 30.
[50] Wasserheit, J.N.; Aral, S.O., The dynamic topology of sexually transmitted disease epidemics: implications for prevention strategies, Journal of infectious diseases, 174, 2, S201-S213, (1996)
[51] Zimmerman, R., AIDS’s spread inflames other crises, Wall street journal, November 27, (2002)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.