Using the SaTScan method to detect local malaria clusters for guiding malaria control programmes

Coleman, Michael ORCID: https://orcid.org/0000-0003-4186-3526, Mabuza, A. M., Kok, G., Coetzee, M., Durrheim, D. N. and Coleman, Marlize (2009) 'Using the SaTScan method to detect local malaria clusters for guiding malaria control programmes'. Malaria Journal, Vol 8, Issue 1.

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Abstract

Background: Mpumalanga Province, South Africa is a low malaria transmission area that is subject to malaria epidemics. SaTScan methodology was used by the malaria control programme to detect local malaria clusters to assist disease control planning. The third season for case cluster identification overlapped with the first season of implementing an outbreak identification and response system in the area. Methods: SaTScan (TM) software using the Kulldorf method of retrospective space-time permutation and the Bernoulli purely spatial model was used to identify malaria clusters using definitively confirmed individual cases in seven towns over three malaria seasons. Following passive case reporting at health facilities during the 2002 to 2005 seasons, active case detection was carried out in the communities, this assisted with determining the probable source of infection. The distribution and statistical significance of the clusters were explored by means of Monte Carlo replication of data sets under the null hypothesis with replications greater than 999 to ensure adequate power for defining clusters. Results and discussion: SaTScan detected five space-clusters and two space-time clusters during the study period. There was strong concordance between recognized local clustering of cases and outbreak declaration in specific towns. Both Albertsnek and Thambokulu reported malaria outbreaks in the same season as space-time clusters. This synergy may allow mutual validation of the two systems in confirming outbreaks demanding additional resources and cluster identification at local level to better target resources. Conclusion: Exploring the clustering of cases assisted with the planning of public health activities, including mobilizing health workers and resources. Where appropriate additional indoor residual spraying, focal larviciding and health promotion activities, were all also carried out.

Item Type:	Article
Uncontrolled Keywords:	article cluster analysis computer program epidemic health care facility health program malaria control satscan South Africa geography health survey human infection control malaria methodology mosquito theoretical model Disease Notification Disease Outbreaks Humans Models, Theoretical Mosquito Control Population Surveillance Software Space-Time Clustering
Subjects:	WA Public Health > WA 20.5 Research (General) WC Communicable Diseases > Tropical and Parasitic Diseases > WC 755 Epidemiology WC Communicable Diseases > Tropical and Parasitic Diseases > WC 750 Malaria QX Parasitology > Insects. Other Parasites > QX 650 Insect vectors WA Public Health > Preventive Medicine > WA 110 Prevention and control of communicable diseases. Transmission of infectious diseases W General Medicine. Health Professions > W 26.5 Informatics. Health informatics QX Parasitology > Insects. Other Parasites > QX 510 Mosquitoes WA Public Health > Statistics. Surveys > WA 950 Theory or methods of medical statistics. Epidemiologic methods QX Parasitology > Insects. Other Parasites > QX 600 Insect control. Tick control WA Public Health > WA 105 Epidemiology
Faculty: Department:	Groups (2002 - 2012) > Vector Group
Digital Object Identifer (DOI):	https://doi.org/10.1186/1475-2875-8-68
Depositing User:	Users 183 not found.
Date Deposited:	22 Jun 2010 09:43
Last Modified:	06 Feb 2018 12:59
URI:	https://archive.lstmed.ac.uk/id/eprint/245

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