The contribution of spatial analysis to understanding HIV/TB mortality in children: a structural equation modelling approach

References

• UNAIDS. Report on the global AIDS epidemic 2011. Available from: http://www.avert.org/africa-hiv-aids-statistics.htm [cited 23 October 2012].
   Google Scholar
• WHO. One million lives can be saved between now and the end of 2015 by preventing and treating tuberculosis among people living with HIV.. Available from: http://www.who.int/tb/challenges/hiv/fastfactsbrochure.pdf [cited 23 October 2012]..
   Google Scholar
• Statistics South Africa (StatsSA). Statistical release P0302 2011. Available from: http://www.statssa.gov.za/publications/P0302/P03022011.pdf [cited 23 October 2012].
   Google Scholar
• Bradshaw D, Bourne D, Nannan N. What are the leading causes of death among South African children. MRC Policy Brief & Unicef. 2003; 3: 1–4.
   Google Scholar
• Doherty T, Sanders D, Goga A, Jackson D. Implications of the new WHO guidelines on HIV and infant feeding for child survival in South Africa. Bull World Health Organ. 2011; 89: 62–7.10.3402/gha.v6i0.19266.
   Web of Science ®Google Scholar
• UNICEF. State of the World's Children year 2009. Available from: http://www.unicef.org/publications/index_47127.html [cited 23 October 2012].
   Google Scholar
• Waller LA, Gotway CA. Applied spatial statistics for public health data. Wiley. Atlanta GA, 2004
   Google Scholar
• Mosley WH, Chen LC. An analytical framework for the study of child survival in developing countries. Popul Dev Rev. 1984; 10: 25–45.10.3402/gha.v6i0.19266.
   Web of Science ®Google Scholar
• Rutstein SO. Factors associated with trends in infant and child mortality in developing countries in the 1990s. Bull World Health Organ. 2000; 78: 1256–70.
   PubMed Web of Science ®Google Scholar
• Filteau S. The HIV-exposed, uninfected African child. Trop Med Int Health. 2009; 14: 276–87.10.3402/gha.v6i0.19266.
   PubMed Web of Science ®Google Scholar
• Guerrero L, La Valley A. Conflict, emotion, and communication. The SAGE handbook of conflict communication: integrating theory, research, and practice. Oetzel JG, Ting-Toomey SSAGE. Thousand Oaks CA, 2006; 69–96.
   Google Scholar
• Hargreaves J, Collinson M, Kahn K, Clark S, Tollman S. Childhood mortality among former Mozambican refugees and their hosts in rural South Africa. Int J Epidemiol. 2004; 33: 1271–8.10.3402/gha.v6i0.19266.
   PubMed Web of Science ®Google Scholar
• Marshall RJ. A review of methods for the statistical analysis of spatial patterns of disease. J Roy Stat Soc Series A (Statistics in Society). 1991; 154: 421–41.10.3402/gha.v6i0.19266.
   Web of Science ®Google Scholar
• Gosoniu L, Vounatsou P, Tami A, Nathan R, Grundmann H, Lengeler C. Spatial effects of mosquito bednets on child mortality. BMC Publ Health. 2008; 8: 356.10.3402/gha.v6i0.19266.
   PubMed Web of Science ®Google Scholar
• Moonan PK, Bayona M, Quitugua TN, Oppong J, Dunbar D, Jost KC, et al.. Using GIS technology to identify areas of tuberculosis transmission and incidence. Int J Health Geogr. 2004; 3: 23.10.3402/gha.v6i0.19266.
   PubMedGoogle Scholar
• Sartorius B, Kahn K, Vounatsou P, Collinson M, Tollman S. Young and vulnerable: spatial-temporal trends and risk factors for infant mortality in rural South Africa (Agincourt), 1992–2007. BMC Publ Health. 2010; 10: 645.10.3402/gha.v6i0.19266.
   PubMed Web of Science ®Google Scholar
• Middelkoop K, Bekker LG, Morrow C, Zwane E, Wood R. Childhood tuberculosis infection and disease: a spatial and temporal transmission analysis in a South African township. S Afr Med J. 2009; 99: 738–43.
   PubMed Web of Science ®Google Scholar
• Tanser F, LeSueur D, Solarsh G, Wilkinson D. HIV heterogeneity and proximity of homestead to roads in rural South Africa: an exploration using a geographical information system. Trop Med Int Health. 2000; 5: 40–6.10.3402/gha.v6i0.19266.
   PubMed Web of Science ®Google Scholar
• Musenge E, Vounatsou P, Kahn K. Space-time confounding adjusted determinants of child HIV/TB mortality for large zero-inflated data in rural South Africa. Spat Spatio-temporal Epidemiol. 2011; 2: 205–17.10.3402/gha.v6i0.19266.
   Google Scholar
• Kahn K, Tollman SM, Collinson MA, Clark SJ, Twine R, Clark BD, et al.. Research into health, population and social transitions in rural South Africa: data and methods of the Agincourt Health and Demographic Surveillance System. Scand J Publ Health. 2007; 35: 8–20.10.3402/gha.v6i0.19266.
   Web of Science ®Google Scholar
• Clark SJ, Collinson MA, Kahn K, Drullinger K, Tollman SM. Returning home to die: circular labour migration and mortality in South Africa. Scand J Public Health Suppl. 2007; 69: 35–44.10.3402/gha.v6i0.19266.
   PubMedGoogle Scholar
• Kahn K, Tollman SM, Garenne M, Gear JS. Validation and application of verbal autopsies in a rural area of South Africa. Trop Med Int Health. 2000; 5: 824–31.10.3402/gha.v6i0.19266.
   PubMed Web of Science ®Google Scholar
• Tollman SM, Kahn K, Sartorius B, Collinson MA, Clark SJ, Garenne ML. Implications of mortality transition for primary health care in rural South Africa: a population-based surveillance study. Lancet. 2008; 372: 893–901.10.3402/gha.v6i0.19266.
   PubMed Web of Science ®Google Scholar
• Meade MS. Medical geography as human ecology: the dimension of population movement. Geogr Rev. 1977; 67: 379–93.10.3402/gha.v6i0.19266.
   Web of Science ®Google Scholar
• Lewis JJC, Donnelly CA, Mare P, Mupambireyi Z, Garnett GP, Gregson S. Evaluating the proximate determinants framework for HIV infection in rural Zimbabwe. Sex Transm Infect. 2007; 83: i61–9.10.3402/gha.v6i0.19266.
   PubMed Web of Science ®Google Scholar
• Boerma J, Weir SS. Integrating demographic and epidemiological approaches to research on HIV/AIDS: the proximate-determinants framework. J Infec Dis. 2005; 191: S61.10.3402/gha.v6i0.19266.
   PubMed Web of Science ®Google Scholar
• Lopman B, Nyamukapa C, Mushati P, Mupambireyi Z, Mason P, Garnett GP, et al.. HIV incidence in 3 years of follow-up of a Zimbabwe cohort—1998–2000 to 2001–03: contributions of proximate and underlying determinants to transmission. Int J Epidemiol. 2008; 37: 88–105.10.3402/gha.v6i0.19266.
   PubMed Web of Science ®Google Scholar
• Cressie NAC. Statistics for spatial data. Wiley. New York, 1993
   Google Scholar
• Banerjee S, Carlin BP, Gelfand AE. Hierarchical modeling and analysis for spatial data. Chapman & Hall/CRC. Boca Raton FL, 2004
   Google Scholar
• Stata Corporation. Stata statistical software release 10. College StationTX: Stata Corporation LP. 2007.
   Google Scholar
• Kimani-Murage EW, Manderson L, Norris SA, Kahn K. ‘You opened our eyes’: care-giving after learning a child's positive HIV status in rural South Africa. Health Soc Care Community. 2010; 18: 264–71.
   PubMed Web of Science ®Google Scholar
• Belitz C, Brezger A, Kneib T, Lang S, Fronk E, Heinzl F, et al.Bayesx-software for bayesian inference in structured additive regression models. 2011. Version 2.01. Available from: http://www.stat.uni-muenchen.de/∼bayesx [cited 23 October 2012]..
   Google Scholar
• Coetzee D, Hilderbrand K, Boulle A, Draper B, Abdullah F, Goemaere E. Effectiveness of the first district-wide programme for the prevention of mother-to-child transmission of HIV in South Africa. Bull World Health Organ. 2005; 83: 489–94.
   PubMed Web of Science ®Google Scholar
• National Department of Health. Clinical guidelines: prevention of mother-to-child transmission (PMTCT) 2010. Available from: http://wwwfidssacoza/images/PMTCT_Guidelinespdf [cited 23 October 2012]..
   Google Scholar
• Ndirangu J, Newell M-L, Tanser F, Herbst AJ, Bland R. Decline in early life mortality in a high HIV prevalence rural area of South Africa: evidence of HIV prevention or treatment impact?. AIDS. 2010; 24: 593–602.10.3402/gha.v6i0.19266.
   PubMed Web of Science ®Google Scholar
• Katapa R. A comparison of female-and male-headed households in Tanzania and poverty implications. J Biosoc Sci. 2006; 38: 327.10.3402/gha.v6i0.19266.
   PubMed Web of Science ®Google Scholar
• Wiegers E, Curry J, Garbero A, Hourihan J. Patterns of vulnerability to AIDS impacts in Zambian households. Dev Change. 2006; 37: 1073–92.10.3402/gha.v6i0.19266.
   Web of Science ®Google Scholar
• Oni S, Obi C, Okorie A, Thabede D, Jordan A. The economic impact of HIV/AIDS on rural households in Limpopo Province. S Afr J Econ. 2002; 70: 551–62.10.3402/gha.v6i0.19266.
   Google Scholar
• Collinson MA. Striving against adversity: the dynamics of migration, health and poverty in rural South Africa. Medical Dissertations, Umeå University, Umeå. 2009
   Google Scholar
• Posel D, Casale D. What has been happening to internal labour migration in South Africa, 1993–1999?. S Afr J Econ. 2003; 71: 455–79.10.3402/gha.v6i0.19266.
   Web of Science ®Google Scholar
• Hahn MB, Riederer AM, Foster SO. The livelihood vulnerability index: a pragmatic approach to assessing risks from climate variability and change--a case study in Mozambique. Global Environ Change. 2009; 19: 74–88.10.3402/gha.v6i0.19266.
   Web of Science ®Google Scholar
• Beguy D, Bocquier P, Zulu EM. Circular migration patterns and determinants in Nairobi slum settlements. Demographic Res. 2010; 23: 549–86.10.3402/gha.v6i0.19266.
   Web of Science ®Google Scholar
• Stata Corporation. Stata statistical software release 12. College StationTX: Stata Corporation LP. 2011.
   Google Scholar
• Kline RB. Principles and practice of structural equation modeling. 3rd ed. Guilford Press. New York, 2011
   Google Scholar
• Bollen KA. Structural equations with latent variables. Wiley. New York, 1989
   Google Scholar
• Bollen KA, Curran PJ. Latent curve models: a structural equation perspective. Wiley-Interscience. New York, 2006
   Google Scholar