Profile: The Karonga Health and Demographic Surveillance System

Crampin, Amelia C.; Dube, Albert; Mboma, Sebastian; Price, Alison; Chihana, Menard; Jahn, Andreas; Baschieri, Angela; Molesworth, Anna; Mwaiyeghele, Elnaeus; Branson, Keith; Floyd, Sian; McGrath, Nuala; Fine, Paul E. M.; French, Neil; Glynn, Judith R.; Żaba, Basia

doi:10.1093/ije/dys088

Cited by 121 publications

(134 citation statements)

References 20 publications

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“…We apply both methods to VA data from two HDSS sites: the Agincourt health and sociodemographic surveillance system (Kahn et al , 2012) and the Karonga health and demographic surveillance system (Crampin et al , 2012). Both sites collect VA data as the primary means of understanding the distribution and dynamics of cause of death.…”

Section: Resultsmentioning

confidence: 99%

Probabilistic Cause-of-Death Assignment Using Verbal Autopsies

McCormick

Calvert

et al. 2016

Journal of the American Statistical Association

149

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In regions without complete-coverage civil registration and vital statistics systems there is uncertainty about even the most basic demographic indicators. In such regions the majority of deaths occur outside hospitals and are not recorded. Worldwide, fewer than one-third of deaths are assigned a cause, with the least information available from the most impoverished nations. In populations like this, verbal autopsy (VA) is a commonly used tool to assess cause of death and estimate cause-specific mortality rates and the distribution of deaths by cause. VA uses an interview with caregivers of the decedent to elicit data describing the signs and symptoms leading up to the death. This paper develops a new statistical tool known as InSilicoVA to classify cause of death using information acquired through VA. InSilicoVA shares uncertainty between cause of death assignments for specific individuals and the distribution of deaths by cause across the population. Using side-by-side comparisons with both observed and simulated data, we demonstrate that InSilicoVA has distinct advantages compared to currently available methods.

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Section: Resultsmentioning

confidence: 99%

Probabilistic Cause-of-Death Assignment Using Verbal Autopsies

McCormick

Calvert

et al. 2016

Journal of the American Statistical Association

149

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“…One site was rural – Chilumba, in southern Karonga district, northern Malawi. The rural study was nested within a demographic surveillance site (DSS) established by MEIRU’s forerunner, the Karonga Prevention Study, in 2002 [25–27]. The other site was an enumerated urban population, in Area 25 within Lilongwe city in central Malawi [25, 27].…”

Section: Methodsmentioning

confidence: 99%

Prevalence and risk factors for anemia severity and type in Malawian men and women: urban and rural differences

Adamu

Crampin

Kayuni

et al. 2017

Popul Health Metrics

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BackgroundThe global burden of anemia is large especially in sub-Saharan Africa, where HIV is common and lifestyles are changing rapidly with urbanization. The effects of these changes are unknown. Studies of anemia usually focus on pregnant women or children, among whom the burden is greatest. We describe prevalence and risk factors for anemia among rural and urban men and women of all ages in Malawi.MethodsWe analyzed data from a population-wide cross-sectional survey of adults conducted in two sites, Karonga (rural) and Lilongwe (urban), commencing in May 2013. We used multinomial logistic regression models, stratified by sex to identify risk factors for mild and moderate-to-severe anemia.ResultsAnemia prevalence was assessed among 8,926 men (age range 18–100 years) and 14,978 women (age range: 18–103 years). Weighted prevalence levels for all, mild, and moderate-to-severe anemia were 8.2, 6.7 and 1.2% in rural men; 19.4, 12.0 and 7.4% in rural women; 5.9, 5.1 and 0.8% in urban men; and 23.4, 13.6 and 10.1% in urban women. Among women, the odds of anemia were higher among urban residents and those with higher socioeconomic status. Increasing age was associated with higher anemia prevalence in men. Among both men and women, HIV infection was a consistent risk factor for severity of anemia, though its relative effect was stronger on moderate-to-severe anemia.ConclusionsThe drivers of anemia in this population are complex, include both socioeconomic and biological factors and are affecting men and women differently. The associations with urban lifestyle and HIV indicate opportunities for targeted intervention.

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“…The Karonga HDSS was established in 2002 and captures births, deaths, and in- and out-migrations in a population of about 39,000 people living in a 150 km 2 rural area [20]. All deaths are assessed using a verbal autopsy, and information on each individual’s socio-economic status is collected annually.…”

Section: Methodsmentioning

confidence: 99%

Implementing electronic data capture at a well-established health and demographic surveillance site in rural northern Malawi

McLean

Dube

Saul

et al. 2017

Global Health Action

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This article aims to assess multiple issues of resources, staffing, local opinion, data quality, cost, and security while transitioning to electronic data collection (EDC) at a long-running community research site in northern Malawi. Levels of missing and error fields, delay from data collection to availability, and average number of interviews per day were compared between EDC and paper in a complex, repeated annual household survey. Three focus groups with field and data staff with experience using both methods, and in-depth interviews with participants were carried out. Cost for each method were estimated and compared. Missing data was more common on paper questionnaires than on EDC, and a similar number were carried out per day. Fieldworkers generally preferred EDC, but data staff feared for their employment. Most respondents had no strong preference for a method. The cost of the paper system was estimated to be higher than using EDC. The existing infrastructure and technical expertise could be adapted to using EDC, but changes have an impact on data processing jobs as fewer, and better qualified staff are required. EDC is cost-effective, and, for a long-running site, may offer further savings, as devices can be used in multiple studies and perform several other functions. EDC is accepted by fieldworkers and respondents, has good levels of quality and timeliness, and security can be maintained. EDC is well-suited for use in a well-established research site using and developing existing infrastructure and expertise.

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Profile: The Karonga Health and Demographic Surveillance System

Cited by 121 publications

References 20 publications

Probabilistic Cause-of-Death Assignment Using Verbal Autopsies

Probabilistic Cause-of-Death Assignment Using Verbal Autopsies

Prevalence and risk factors for anemia severity and type in Malawian men and women: urban and rural differences

Implementing electronic data capture at a well-established health and demographic surveillance site in rural northern Malawi

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