Spatial distribution of death cases (A), population of children younger than 5 years old (B), and long lasting insecticide net distribution (C) in the study area across the study period.

<p>Kernel estimation of the probability density function for each grid was calculated in terms of death cases, child population and long lasting insecticide treated nets using the quartic kernel function with the fixed bandwidth of 1000 meter. For visualizing the estimated probabilities by the kernel estimation, the probabilities were classified into 20 groups and describes on the grid of the map. The 20 groups were colored by rainbow color: the lowest group in blue, the middle group in green, and the highest group in red. Black dots in (A) are observed death cases.</p

Trends in risk on all causes of child mortality (ACCM) for non-net user children across long lasting insecticide nets (LLINs) density quartiles (A) and those across density quartiles of young people (B) for children who live in a house far from health facilities (Remote dataset^*).

<p>The best fit model was the 1000-meter radius model in trend analyses and the trend was 1.25 (95%CI 1.03–1.51) for LLIN density quartiles and 0.77 (95%CI 0.63–0.94) for density quartiles of young people. ^* Remote dataset: Dataset retrieved children of households located far from health facilities more than 3 kilometers from the district hospital or more than 1 kilometer from health centers and dispensaries in the area. Solid lines are point estimates of hazard ratios for Cox PH models within a radius from 100 meters to 3,000 meters and dotted vertical lines show the best fit model according to likelihood among models. Among the models both in (A) and (B), the best fit mode was the 1000-meter radius model (dotted vertical line). Gray bands indicate 95% confidence intervals for each point estimate.</p

Mortalities and person-years by bed net type and study period for the whole cohort.

<p>Mortalities and person-years by bed net type and study period for the whole cohort.</p

Bed net usage proportions during survey periods among individuals younger than 65 years (A) and among children younger than 5 years (B), according to the type of bed net used.

<p>Orange line, total bed nets; blue line, long lasting insecticide nets (LLIN); green line, untreated nets; dark red line, any bed net. Moving averages were calculated using five age groups to create graphs with smooth lines. Period I = October 14, 2008, to December 19, 2008; period II = May 11, 2009, to June 4, 2009; period III = January 7, 2010, to March 2, 2010; and period IV = September 22, 2010, to December 3, 2010.</p

Health and Demographic Surveillance System in the Western and Coastal Areas of Kenya: An Infrastructure for Epidemiologic Studies in Africa

Background: The Health and Demographic Surveillance System (HDSS) is a longitudinal data collection process that systematically and continuously monitors population dynamics for a specified population in a geographically defined area that lacks an effective system for registering demographic information and vital events. Methods: HDSS programs have been run in 2 regions in Kenya: in Mbita district in Nyanza province and Kwale district in Coast Province. The 2 areas have different disease burdens and cultures. Vital events were obtained by using personal digital assistants and global positioning system devices. Additional health-related surveys have been conducted bimonthly using various PDA-assisted survey software. Results: The Mbita HDSS covers 55 929 individuals, and the Kwale HDSS covers 42 585 individuals. In the Mbita HDSS, the life expectancy was 61.0 years for females and 57.5 years for males. Under-5 mortality was 91.5 per 1000 live births, and infant mortality was 47.0 per 1000 live births. The total fertility rate was 3.7 per woman. Data from the Kwale HDSS were not available because it has been running for less than 1 year at the time of this report. Conclusions: Our HDSS programs are based on a computer-assisted survey system that provides a rapid and flexible data collection platform in areas that lack an effective basic resident registration system. Although the HDSS areas are not representative of the entire country, they provide a base for several epidemiologic and social study programs, and for practical community support programs that seek to improve the health of the people in these areas

Schematic illustration for calculation of bed nets and population densities around a child.

<p>All individuals and all households within a given radius from 100 to 3,000 meters around each child were retrieved using the geographical position (longitude and latitude) of each household by GPS recorded in HDSS dataset in each survey period (period I, II, III, and IV).</p

Adjusted hazard ratios (HRs) of densities of long lasting insecticide nets (LLINs) on all causes of child mortality (ACCM) for children sleeping without a bed net using the whole dataset ^*(A) and for children limited to those who lived far from health facilities using the remote dataset^** (B). Reference is the lowest LLIN density quartile group of children.

<p>^*Whole dataset: Dataset covering the whole study area. ^**Remote dataset: Dataset retrieved children of households located more than 3 kilometers from the district hospital or more than 1 kilometer from health centers and dispensaries in the area. Solid lines are point estimates of hazard ratios for Cox PH models within a radius from 100 meters to 3,000 meters and dotted vertical lines show the best fit model according to likelihood among models. Among the models in (A), the best fit mode was the 900-meter radius model (the dotted vertical line) and among the models in (B), it was the 2300-meter radius model (dotted vertical line). Gray bands indicate 95% confidence intervals for each point estimate.</p

Age distributions (in months) of children by sex and bed net type.

*<p>Whole dataset: the dataset of whole children.</p>**<p>Remote dataset: Dataset that excluded children whose house were located within three kilometers from the district hospital; or within one kilometer from health centers, dispensaries, and clinics to remove the effect of townships where lower child mortality was expected due to easy access to health facilities.</p

Adjusted hazard ratios (HRs) of densities of young population densities on all causes of child mortality (ACCM) for children sleeping without a bed net using the whole dataset ^* (A) for children limited to those who lived far from health facilities using the remote dataset^** (B). Reference is the lowest young population density quartile group of children.

<p>^* Whole dataset: Dataset covering the whole study area. ^** Remote dataset: Dataset retrieved children of households located far from health facilities more than 3 kilometers from the district hospital or more than 1 kilometer from health centers and dispensaries in the area. Solid lines are point estimates of hazard ratios for Cox PH models within a radius from 100 meters to 3,000 meters and dot vertical lines show the best fit model according to likelihood among models. Among the models in (A), the best fit model was the 900-meter radius model (dotted vertical line) and among the models in (B), it was the 2300-meter radius model (dotted vertical line). Gray bands indicate 95% confidence intervals for each point estimate.</p

Are Long-Lasting Insecticidal Nets Effective for Preventing Childhood Deaths among Non-Net Users? A Community-Based Cohort Study in Western Kenya

BackgroundIncreasing the distribution and use of insecticide-treated nets (ITNs) in Sub-Saharan Africa has made controlling malaria with ITNs more practical. We evaluated community effects induced by ITNs, specifically long-lasting insecticidal nets (LLINs), under ordinary conditions in an endemic malaria area of Western Kenya.MethodsUsing the database from Mbita Health and Demographic Surveillance System (HDSS), children younger than 5 years old were assessed over four survey periods. We analyzed the effect of bed net usage, LLIN density and population density of young people around a child on all-cause child mortality (ACCM) rates using Cox PH models.ResultsDuring the study, 14,554 children were followed and 250 deaths were recorded. The adjusted hazard ratios (HRs) for LLIN usage compared with no net usage were not significant among the models: 1.08 (95%CI 0.76–1.52), 1.19 (95%CI 0.69–2.08) and 0.92 (95%CI 0.42–2.02) for LLIN users, untreated net users, and any net users, respectively. A significant increasing linear trend in risk across LLIN density quartiles (HR = 1.25; 95%CI 1.03–1.51) and a decreasing linear trend in risk across young population density quartiles among non-net user children (HR = 0.77; 95%CI 0.63–0.94) were observed.ConclusionsAlthough our data showed that current LLIN coverage level (about 35%) could induce a community effect to protect children sleeping without bed nets even in a malaria-endemic area, it appears that a better system is needed to monitor the current malaria situation globally in order to optimize malaria control programs with limited resources