Clustering of childhood mortality in the Kintampo Health and Demographic Surveillance System in Ghana

Background: Childhood mortality in Ghana has generally declined in the last four decades. However, estimates tend to conceal substantial variability among regions and districts. The lack of population-based data in Ghana, as in other less developed countries, has hindered the development of effective programmes targeted specifically at clusters where mortality levels are significantly higher. Objective: This paper seeks to test for the existence of statistically significant clusters of childhood mortality within the Kintampo Health and Demographic Surveillance System (KHDSS) between 2005 and 2007. Design: In this study, mortality rates were generated using mortality data extracted from the health and demographic surveillance database of the KHDSS and exported into STATA. The spatial and spatio-temporal scan statistic by Kulldorff was used to identify significant clusters of childhood mortality within the KHDSS. Results: A significant cluster of villages with high under-five mortality in the south-eastern part of the KHDSS in 2006 was identified. This is a remote location where poverty levels are relatively higher, health facilities are more sparse and these are compounded by poor transport services in case of emergencies. Conclusion: This study highlights the potential of the surveillance platform to demonstrate the spatial dimensions of childhood mortality clustering. It is apparent, though, that further studies need to be carried out in order to explore the underlying risk factors for potential mortality clusters that could emerge later

User evaluation indicates high quality of the Surveillance Outbreak Response Management and Analysis System (SORMAS) after field deployment in Nigeria in 2015 and 2018

During the West African Ebola virus disease outbreak in 2014-15, health agencies had severe challenges with case notification and contact tracing. To overcome these, we developed the Surveillance, Outbreak Response Management and Analysis System (SORMAS). The objective of this study was to measure perceived quality of SORMAS and its change over time. We ran a 4-week-pilot and 8-week-implementation of SORMAS among hospital informants in Kano state, Nigeria in 2015 and 2018 respectively. We carried out surveys after the pilot and implementation asking about usefulness and acceptability. We calculated the proportions of users per answer together with their 95% confidence intervals (CI) and compared whether the 2015 response distributions differed from those from 2018. Total of 31 and 74 hospital informants participated in the survey in 2015 and 2018, respectively. In 2018, 94% (CI: 89-100%) of users indicated that the tool was useful, 92% (CI: 86-98%) would recommend SORMAS to colleagues and 18% (CI: 10-28%) had login difficulties. In 2015, the proportions were 74% (CI: 59-90%), 90% (CI: 80-100%), and 87% (CI: 75-99%) respectively. Results indicate high usefulness and acceptability of SORMAS. We recommend mHealth tools to be evaluated to allow repeated measurements and comparisons between different versions and users

Surveillance and Outbreak Response Management System (SORMAS) to support the control of the Ebola virus disease outbreak in West Africa

In the context of controlling the current outbreak of Ebola virus disease (EVD), the World Health Organization claimed that ‘critical determinant of epidemic size appears to be the speed of implementation of rigorous control measures’, i.e. immediate follow-up of contact persons during 21 days after exposure, isolation and treatment of cases, decontamination, and safe burials. We developed the Surveillance and Outbreak Response Management System (SORMAS) to improve efficiency and timeliness of these measures. We used the Design Thinking methodology to systematically analyse experiences from field workers and the Ebola Emergency Operations Centre (EOC) after successful control of the EVD outbreak in Nigeria. We developed a process model with seven personas representing the procedures of EVD outbreak control. The SORMAS system architecture combines latest In-Memory Database (IMDB) technology via SAP HANA (in-memory, relational database management system), enabling interactive data analyses, and established SAP cloud tools, such as SAP Afaria (a mobile device management software). The user interface consists of specific front-ends for smartphones and tablet devices, which are independent from physical configurations. SORMAS allows real-time, bidirectional information exchange between field workers and the EOC, ensures supervision of contact follow-up, automated status reports, and GPS tracking. SORMAS may become a platform for outbreak management and improved routine surveillance of any infectious disease. Furthermore, the SORMAS process model may serve as framework for EVD outbreak modelling

SerpinA3N is a novel hypothalamic gene upregulated by a high-fat diet and leptin in mice

Background: Energy homeostasis is regulated by the hypothalamus but fails when animals are fed a high-fat diet (HFD), and leptin insensitivity and obesity develops. To elucidate the possible mechanisms underlying these effects, a microarray-based transcriptomics approach was used to identify novel genes regulated by HFD and leptin in the mouse hypothalamus. Results: Mouse global array data identified serpinA3N as a novel gene highly upregulated by both a HFD and leptin challenge. In situ hybridisation showed serpinA3N expression upregulation by HFD and leptin in all major hypothalamic nuclei in agreement with transcriptomic gene expression data. Immunohistochemistry and studies in the hypothalamic clonal neuronal cell line, mHypoE-N42 (N42), confirmed that alpha 1-antichymotrypsin (α1AC), the protein encoded by serpinA3, is localised to neurons and revealed that it is secreted into the media. SerpinA3N expression in N42 neurons is upregulated by palmitic acid and by leptin, together with IL-6 and TNFα, and all three genes are downregulated by the anti-inflammatory monounsaturated fat, oleic acid. Additionally, palmitate upregulation of serpinA3 in N42 neurons is blocked by the NFκB inhibitor, BAY11, and the upregulation of serpinA3N expression in the hypothalamus by HFD is blunted in IL-1 receptor 1 knockout (IL-1R1−/−) mice. Conclusions: These data demonstrate that serpinA3 expression is implicated in nutritionally mediated hypothalamic inflammation

Climate-Based Models for Understanding and Forecasting Dengue Epidemics

Dengue fever is a major public health problem in the tropics and subtropics. Since no vaccine exists, understanding and predicting outbreaks remain of crucial interest. Climate influences the mosquito-vector biology and the viral transmission cycle. Its impact on dengue dynamics is of growing interest. We analyzed the epidemiology of dengue in Noumea (New Caledonia) from 1971 to 2010 and its relationships with local and remote climate conditions using an original approach combining a comparison of epidemic and non epidemic years, bivariate and multivariate analyses. We found that the occurrence of outbreaks in Noumea was strongly influenced by climate during the last forty years. Efficient models were developed to estimate the yearly risk of outbreak as a function of two meteorological variables that were contemporaneous (explicative model) or prior (predictive model) to the outbreak onset. Local threshold values of maximal temperature and relative humidity were identified. Our results provide new insights to understand the link between climate and dengue outbreaks, and have a substantial impact on dengue management in New Caledonia since the health authorities have integrated these models into their decision making process and vector control policies. This raises the possibility to provide similar early warning systems in other countries

Young and vulnerable: Spatial-temporal trends and risk factors for infant mortality in rural South Africa (Agincourt), 1992-2007

<p>Abstract</p> <p>Background</p> <p>Infant mortality is an important indicator of population health in a country. It is associated with several health determinants, such as maternal health, access to high-quality health care, socioeconomic conditions, and public health policy and practices.</p> <p>Methods</p> <p>A spatial-temporal analysis was performed to assess changes in infant mortality patterns between 1992-2007 and to identify factors associated with infant mortality risk in the Agincourt sub-district, rural northeast South Africa. Period, sex, refugee status, maternal and fertility-related factors, household mortality experience, distance to nearest primary health care facility, and socio-economic status were examined as possible risk factors. All-cause and cause-specific mortality maps were developed to identify high risk areas within the study site. The analysis was carried out by fitting Bayesian hierarchical geostatistical negative binomial autoregressive models using Markov chain Monte Carlo simulation. Simulation-based Bayesian kriging was used to produce maps of all-cause and cause-specific mortality risk.</p> <p>Results</p> <p>Infant mortality increased significantly over the study period, largely due to the impact of the HIV epidemic. There was a high burden of neonatal mortality (especially perinatal) with several hot spots observed in close proximity to health facilities. Significant risk factors for all-cause infant mortality were mother's death in first year (most commonly due to HIV), death of previous sibling and increasing number of household deaths. Being born to a Mozambican mother posed a significant risk for infectious and parasitic deaths, particularly acute diarrhoea and malnutrition.</p> <p>Conclusions</p> <p>This study demonstrates the use of Bayesian geostatistical models in assessing risk factors and producing smooth maps of infant mortality risk in a health and socio-demographic surveillance system. Results showed marked geographical differences in mortality risk across a relatively small area. Prevention of vertical transmission of HIV and survival of mothers during the infants' first year in high prevalence villages needs to be urgently addressed, including expanded antenatal testing, prevention of mother-to-child transmission, and improved access to antiretroviral therapy. There is also need to assess and improve the capacity of district hospitals for emergency obstetric and newborn care. Persisting risk factors, including inadequate provision of clean water and sanitation, are yet to be fully addressed.</p

The Health and Demographic Surveillance System (HDSS) in Nouna, Burkina Faso, 1993–2007

The Nouna Health and Demographic Surveillance System (HDSS) is located in rural Burkina Faso and has existed since 1992. Currently, it has about 78,000 inhabitants. It is a member of the International Network for the Demographic Evaluation of Populations and Their Health in Developing Countries (INDEPTH), a global network of members who conducts longitudinal health and demographic evaluation of populations in low- and middle-income countries. The health facilities consist of one hospital and 13 basic health centres (locally known as CSPS). The Nouna HDSS has been used as a sampling frame for numerous studies in the fields of clinical research, epidemiology, health economics, and health systems research. In this paper we review some of the main findings, and we describe the effects that almost 20 years of health research activities have shown in the population in general and in terms of the perception, economic implications, and other indicators. Longitudinal data analyses show that childhood, as well as overall mortality, has significantly decreased over the observation period 1993–2007. The under-five mortality rate dropped from about 40 per 1,000 person-years in the mid-1990s to below 30 per 1,000 in 2007. Further efforts are needed to meet goal four of the Millennium Development Goals, which is to reduce the under-five mortality rate by two-thirds between 1990 and 2015