Spatial variation and hot-spots of district level diarrhea incidences in Ghana: 2010-2014

Epidemiology and future risk estimates of cutaneous leishmaniasis in district Dera Ismail Khan, Pakistan: analysis of data from 2019-2022

Background

Cutaneous leishmaniasis (CL), despite not being a life-threatening condition, has a devastating impact on the public health. CL is widely distributed, exhibiting a distinct epidemiological pattern all over the world. The aim of this study was to investigate CL in District Dera Ismail Khan, Khyber Pakhtunkhwa, Pakistan, and to estimate the risk of epidemics.

Objectives

Materials and Methods

From 2019 to 2022, 1135 CL patients' epidemiological data were collected from district health facilities. For epidemiological characterization, descriptive statistics were used. The spatial analysis was done using ArcGIS V.10.3. The relationship between CL occurrence and climatic variables was investigated using liner regression analysis.

Results

Between 2019 and 2022, there was a decline in the annual CL incidence trend. Males and people under the age of 20 were particularly susceptible. A total of 1204 lesions were identified, with 76.1% of individuals having a single lesion and 23.9% having multiple lesions. Most of the lesions were nodular and ulcerative in nature and were found on exposed body parts such as the lower extremity (34.2%) and the face (30.7%). A choropleth map revealed an increased incidence of CL in Tehsil D.I.K (63%) and Paharpur (10%). According to a digital elevation model, high altitudes have a lower prevalence of CL. For focal transmission and high-risk zones, Inverse Density Weight (IDW) spatial interplation, focal statistics, cluster, and outlier analysis validated that CL cases were high in D.I.K, Kulachi, and Paharpur tehsils. Increased temperature, relative humidity, and precipitation were not significantly associated with CL infection.

Conclusions

The study provided essential details for public health sectors to develop intervention strategies for future CL outbreaks.

Has Ghana's Rotavirus Vaccine Switch Met Programmatic Expectations? An Analysis of National Surveillance Data; 2018-2022

Background

Ghana introduced a 2-dose schedule rotavirus vaccine, Rotarix, into childhood immunization in 2012 but switched to a 3-dose schedule vaccine, Rotavac, in 2020 on account of programmatic advantages offered by the latter, including lower cost per fully immunized child and lower cold chain volume requirement. The objective of the study was to assess the effect of the vaccine switch on the trends of rotavirus vaccine uptake and health facility outpatient department (OPD) attendance due to diarrhea among children aged 1-11 months.

Methods

A retrospective analysis was conducted on childhood immunization and diarrhea surveillance data for 2018-2022. The uptake of the different rotavirus vaccine products and the proportion of health facility OPD attendance attributed to diarrhea, respectively, were compared between the pre- and postswitch study periods.

Results

The uptake of rotavirus vaccine was sustained following the switch. There were no significant differences in vaccination coverages (rota1, Rotarix coverage [94.3%], vs rota1, Rotavac coverage [95.3%]; P = .757; rota2, Rotarix coverage [91.3%], vs rota2, Rotavac coverage [92.7%]; P = .789). The proportions of health facility OPD attendance due to diarrhea were comparable (preswitch [12.4%] vs postswitch [12.1%]; P = .838).

Conclusions

Ghana's rotavirus vaccine switch yielded expected programmatic benefits without any untoward effects. The trends of vaccine uptake and reduction in diarrhea morbidity were sustained. These experiences and lessons from the rotavirus vaccine switch are vital for potential switches for other vaccines in the current immunization schedule to mitigate the annual vaccine expenditure.

Spatio-temporal distributions and determinants of diarrhea among under-five children in Ethiopia

Objective

The purpose of this study was to evaluate the spatio-temporal pattern of Ethiopia's childhood diarrheal disease and identify its contributing factors.

Methods

We conducted analyses on secondary data from four Ethiopian Demographic and Health Surveys conducted between 2000 and 2016. Moran's I was used to determine spatial dependence and spatial models were used to evaluate variables associated with diarrhea in under-five children at the zonal level.

Results

Childhood diarrhea showed spatial clustering in Ethiopia (Moran's I; p < 0.05). The spatial regression model revealed significant factors at the zonal level: children born at home (e θ = 1.355, 95% CI: 1.052-1.544, p < 0.001), low birth weight (e θ = 1.18, 95% CI: 1.017-1.691, p < 0.05), and unimproved source of water (e θ = 0.8568, 95% CI: 0.671-1.086, p < 0.01).

Conclusion

The prevalence of diarrhea among under-five children varied over time by zone, with the Assosa, Hundene, and Dire Diwa zones having the highest rates. Home births and low birth weight contributed to the prevalence of childhood diarrhea. In high-risk zones of Ethiopia, reducing childhood diarrhea requires integrated child health interventions and raising awareness about the potential hazards associated with unimproved water sources.

A multilevel analysis of the predictors of diarrhea among children under 5 years of age in Eswatini

Diarrhea remains a public health challenge and persistently affect children under 5 years of age, primarily in developing countries. The aim of the study was to investigate the effects of individual, household and community level factors on child diarrhea. Using combined data 2010 and 2014 Eswatini Multiple Indicator Cluster surveys, data for 4,363 under five children was analysed. Univariable, bivariable and multivariable multilevel logistic regression models were used for data analysis. We found that the prevalence of diarrhea was 16.2%, (95% confidence interval (CI): 15.3-18.1). Higher odds of diarrhea were observed among children aged 6-11 months (AOR: 2.67, 95% CI: 1.93, 3.71) and 12-23 months (AOR=2.12, 95% CI: 1.56, 2.87) compared to those aged less than 6 months. However, lower odds of diarrhea were observed among children aged 36-47 months (AOR=0.68, 95% CI: 0.48, 0.97) and 48-59 months (AOR=0.39, 95% CI: 0.26, 0.58), compared to children aged less than 6 months. Children born to mothers aged 35-39 years had lower odds of having diarrhea, (AOR=0.48, 95%CI: 0.30, 0.79) compared to those born to mothers aged 15-19 years. Higher odds of having diarrhea were observed among children from communities with a low proportion of households with improved toilet facility (AOR=1.29, 95% CI: 1.01, 1.66) compared to those from communities with a high proportion of households with improved toilet facility. We found that individual- and community-level factors were associated with child diarrhea in Eswatini. Programmes and policies that aim to mitigate child morbidity due to diarrhea should pay attention to the individual and community factors.

Distribution and Risk of Cutaneous Leishmaniasis in Khyber Pakhtunkhwa, Pakistan

Cutaneous leishmaniasis (CL) is a zoonotic infection caused by obligate intracellular protozoa of the genus Leishmania. This study aimed to investigate CL in Khyber Pakhtunkhwa, Pakistan and to estimate the risk of epidemics. Clinico-epidemiological data of 3188 CL patients were collected from health facilities in 2021. Risk factors were analyzed using the chi-square test. ArcGIS V.10.7.1 was applied for spatial analysis. The association between CL occurrence and climatic variables was examined by Bayesian geostatistical analysis. The clinical data revealed males or individuals younger than 20 years old were more affected. Most patients presented with a single lesion, and the face was the most attacked body part. CL was prevalent in the southern region in winter. A proportional symbol map, a choropleth map, and a digital elevation model map were built to show the distribution of CL. Focal transmission was predicted by inverse distance weighting interpolation. Cluster and outlier analysis identified clusters in Bannu, Dir Lower, and Mardan, and hotspot analysis suggested Bannu as a high-risk foci. Bayesian geostatistical analysis indicated that increasing precipitation and temperature as well as low altitudes were associated with CL infection. The study has provided important information for public health sectors to develop intervention strategies for future CL epidemics.

Spatiotemporal patterns of diarrhea incidence in Ghana and the impact of meteorological and socio-demographic factors

BACKGROUND

Diarrhea remains a significant public health problem and poses a considerable financial burden on Ghana's health insurance scheme. In order to prioritize district-level hotspots of diarrhea incidence for effective targeted interventions, it is important to understand the potential drivers of spatiotemporal patterns of diarrhea. We aimed to identify the spatiotemporal heterogeneity of diarrhea incidence in Ghana and explore how meteorological and socio-demographic factors influence the patterns.

METHODS

We used monthly district-level clinically diagnosed diarrhea data between 2012 and 2018 obtained from the Centre for Health Information and Management of the Ghana Health Services. We utilized a hierarchical Bayesian spatiotemporal modeling framework to evaluate potential associations between district-level monthly diarrhea incidence and meteorological variables (mean temperature, diurnal temperature range, surface water presence) and socio-demographic factors (population density, Gini index, District League Table score) in Ghana. In addition, we investigated whether these associations were consistent across the four agro-ecological zones.

RESULTS

There was considerable spatial heterogeneity in diarrhea patterns across the districts, with clusters of high diarrhea risk areas mostly found in the transition and savannah zones. The average monthly temporal patterns of diarrhea revealed a weak biannual seasonality with major and minor peaks in June and October, respectively, coinciding with the major and minor rainy seasons. We found a significant association between both meteorological and socio-demographic factors and diarrhea risk, but the strength and direction of associations differed across the four agro-ecological zones. Surface water presence demonstrated consistently positive, while diurnal temperature range and population density demonstrated consistently negative associations with diarrhea both overall and across the agro-ecological zones.

CONCLUSIONS

Although overall diarrhea incidence is declining in Ghana, our results revealed high-risk districts that could benefit from district-specific tailored intervention strategies to improve control efforts. Ghana health sector policy-makers can use these results to assess the effectiveness of ongoing interventions at the district level and prioritize resource allocation for diarrhea control.

Neonatal mortality clustering in the central districts of Ghana

INTRODUCTION

Identifying high risk geographical clusters for neonatal mortality is important for guiding policy and targeted interventions. However, limited studies have been conducted in Ghana to identify such clusters.

OBJECTIVE

This study aimed to identify high-risk clusters for all-cause and cause-specific neonatal mortality in the Kintampo Districts.

MATERIALS AND METHODS

Secondary data, comprising of 30,132 singleton neonates between January 2005 and December 2014, from the Kintampo Health and Demographic Surveillance System (KHDSS) database were used. Verbal autopsies were used to determine probable causes of neonatal deaths. Purely spatial analysis was ran to scan for high-risk clusters using Poisson and Bernoulli models for all-cause and cause-specific neonatal mortality in the Kintampo Districts respectively with village as the unit of analysis.

RESULTS

The study revealed significantly high risk of village-clusters for neonatal deaths due to asphyxia (RR = 1.98, p = 0.012) and prematurity (RR = 5.47, p = 0.025) in the southern part of Kintampo Districts. Clusters (emerging clusters) which have the potential to be significant in future, for all-cause neonatal mortality was also identified in the south-western part of the Kintampo Districts.

CONCLUSIONS

Study findings showed cause-specific neonatal mortality clustering in the southern part of the Kintampo Districts. Emerging cluster was also identified for all-cause neonatal mortality. More attention is needed on prematurity and asphyxia in the identified cause-specific neonatal mortality clusters. The emerging cluster for all-cause neonatal mortality also needs more attention to forestall any formation of significant mortality cluster in the future. Further research is also required to understand the high concentration of prematurity and asphyxiated deaths in the identified clusters.

Spatiotemporal patterns of cutaneous leishmaniasis in the district upper and lower Dir, Khyber Pakhtunkhwa, Pakistan: A GIS-based spatial approaches

While Cutaneous leishmaniasis (CL) is not a life-threatening disease, it leads to devastating effects on local community. CL is widely scattered manifesting a noticeable epidemiological pattern around the globe. The present study was planned to address the role of Geographic Information System (GIS) using CL clinico-epidemiological data to determine the high-risk areas of CL. Recorded data (2014-2018) of 3630 positive individuals was collected from Basic Health Units of the Upper and Lower Dir Districts, Khyber Pakhtunkhwa, Pakistan. Descriptive and statistical analysis was used for clinico-epidemiological characterization. For spatial analysis, ArcGIS V.10.3 was used and the CL average incidence was tagged on the proportional, choropleth, and digital elevation model maps. For focal transmission and high-risk zones, Inverse Density Weight (IDW) spatial interpolation, focal statistics, hot spot, cluster and outlier, and Bayesian geostatistical analysis were used. The trend of CL cases was elevated from 2014 to 2016 except for 2017 and 2018. Individuals of both genders younger than 20 years old were highly susceptible. Single lesions were more prominent (56%) and frequently affected facial parts (51%). The size and pretreatment duration of the CL lesion was significantly associated. Spatially, a choropleth map displayed the maximum CL incidences in Tehsil Balambat, Khal, and Termergara (31%-13%) located within a range of 948-1947m elevation in the central regions with proximal CL transmissions. Hot spot and cluster and outlier analysis affirmed that Tehsil Khal was the high-risk CL foci. The Bayesian geostatistical analysis revealed high temperature, less altitude, and annual precipitation as important risk factors. An increasing trend in CL transmission has become evident, affecting both genders and <20 years old children. GIS resolute the concealed CL hubs in the least elevated central regions which warrant the control strategies to restrict future epidemics.

Spatiotemporal and hotspot detection of U5-children diarrhea in resource-limited areas of Ethiopia

Under-five children (U5-children) diarrhea is a significant public health threat, where the World Health Organisation (WHO) reported it as the second leading cause of children's death worldwide. Nearly 1.7 billion cases occur annually with varied temporal and spatial factors. Identification of the spatiotemporal pattern and hotspot areas of U5-children diarrhea can assist targeted intervention and provide an early warning for more effective response measures. This study aimed at examining spatiotemporal variability along with the detection of hotspot areas for U5-children diarrhea in the Bench Maji Zone of southwestern Ethiopia, where resources are limited and cultural heterogeneity is highest. Retrospective longitudinal data of ten years of diarrhea records from January 2008 to December 2017 were used to identify hotspot areas. The incidence rate per 1,000 per year among children was calculated along with seasonal patterns of cases. The spatiotemporal analysis was made using SaTScan version 9.4, while spatial autocorrelations and hotspot identification were generated using ArcGIS 10.5 software. A total of 90,716 U5-children diarrhea cases were reported with an annual incidence rate of 36.1 per 1,000 U5-children, indicating a relative risk (RR) of 1.6 and a log-likelihood ratio (LLR) of 1,347.32 (p < 0.001). The highest incidence of diarrhea illness was recorded during the dry season and showed incidence rate increment from October to February. The risky clusters (RR > 1) were in the districts of Bero, Maji, Surma, Minit Shasha, Guraferda, Mizan Aman Town, and Sheko with annual cases of 127.93, 68.5, 65.12, 55.03, 55.67, 54.14 and 44.97 per 1,000, respectively. The lowest annual cases reported were in the four districts of Shay Bench, South Bench, North Bench, and Minit Goldiya, where RR was less than a unit. Six most likely clusters (Bero, Minit Shasha, Surma, Guraferda, South Bench, and Maji) and one lower RR area (North Bench) were hotspot districts. The U5-children's diarrhea in the study area showed an overall increasing trend during the dry seasons with non-random distribution over space and time. The data recorded during ten years and analyzed with the proper statistical tools helped to identify the hotspot areas with risky seasons where diarrhea could increase.

Rural Ghanaian households are more likely to use alternative unimproved water sources when water from boreholes has undesirable organoleptic characteristics

Sustainable Development Goal (SDG) 6 aims to achieve universal access to safe drinking water sources. However, the health benefits of meeting this goal will only be fully realized if improved sources are used to the exclusion of unimproved sources. Very little is known about how rural African households balance the use of improved and unimproved water sources when multiple options are present. We assessed parallel use of untreated surface water and unimproved hand-dug wells (HDWs) in the presence of boreholes (BHs) using a semi-quantitative water use survey among 750 residents of 15 rural Ghanaian communities, distributed across three BH water quality clusters: control, high salinity, and high iron. Multivariate mixed effects logistic regression models were used to assess the impact of water quality cluster on the use of BHs, HDWs, and surface water, controlling for distance to the nearest source of each type. Reported surface water use was significantly higher in the high salinity and high iron clusters than in the control cluster, especially for water-intensive activities. Respondents in the non-control clusters had approximately eight times higher odds of clothes washing with surface water (p < 0.01) than in the control. Respondents in the high salinity cluster also had 4.3 times higher odds of drinking surface water (p < 0.05). BH use was high in all clusters, but decreased substantially when distance to the nearest BH exceeded 300 m (OR = 0.17-0.25, p < 0.001). Water use from all sources was inversely correlated with distance, with the largest effect observed on HDW use in multivariate models (OR = 0.02, p < 0.001). Surface water and HDW use will likely continue despite the presence of BHs when perceived groundwater quality is poor and other water sources are in close proximity. It is essential to account for naturally-occurring but undesirable groundwater quality parameters in rural water planning to ensure that SDG 6 is met and health benefits are realized.

Geographic differences in maternal and child health care utilization in four Ethiopian regions; a cross-sectional study

BACKGROUND

Maternal and child health (MCH) care utilization often vary with geographic location. We analyzed the geographic distribution and determinants of utilization of four or more antenatal care visits, health facility delivery, child immunization, and care utilization for common childhood illnesses across four Ethiopian regions.

METHODS

A cross-sectional community-based study was employed with two-staged stratified cluster sampling in 46 districts of Ethiopia. A total of 6321 women (13-49 years) and 3110 children below the age of 5 years residing in 5714 households were included. We performed a cluster analysis of the selected MCH care utilization using spatial autocorrelation. We identified district-specific relationships between care coverage and selected factors using geocoded district-level data and ordinary least squares and hotspot analysis using Getis Ord Gi*.

RESULTS

Of the 6321women included in the study, 714 had a live birth in the 12 months before the survey. One-third of the women (30, 95% CI 26-34) had made four or more antenatal visits and almost half of the women (47, 95% CI 43-51) had delivered their most recent child at a health facility. Nearly half of the children (48, 95% CI 40-57) with common childhood illnesses (suspected pneumonia, diarrhoea, or fever) sought care at the health facilities. The proportion of fully immunized children was 41% (95%, CI 37-45). Institutional delivery was clustered at district level (spatial autocorrelation, Moron's I = 0.217, P < 0.01). Full immunization coverage was also spatially clustered (Moron's I = 0.156, P-value < 0.1). Four or more antenatal visits were associated with women's age and parity, while the clustering of institutional delivery was associated with the number of antenatal care visits. Clustering of full immunization was associated with household members owning a mobile phone.

CONCLUSIONS

This study showed evidence for geographic clustering in coverage of health facility deliveries and immunization at the district level, but not in the utilization of antenatal care and utilization of health services for common childhood illnesses. Identifying and improving district-level factors that influenced these outcomes may inform efforts to achieve geographical equitability and universal health coverage.

Geospatial analysis of childhood morbidity in Ghana

INTRODUCTION

Childhood morbidities are common in Ghana. The present study sought to geospatially analyze morbidities among children (0-23 months of age) using five different survey datasets (1993-2014) from the Ghana Demographic and Health Survey.

METHODS

Logistic regression was used to examine childhood morbidity within a place of residence. Then three spatial statistical tools were applied to analyze morbidities among children (0-23 months of age). These tools were: spatial autocorrelation (Global Moran's I)-used to examine clustering or dispersion patterns; cluster and outlier analysis (Anselin's local Moran's I)-to ascertain geographic composition of childhood morbidity clusters and outliers; and hot spot analysis (Getis-Ord G)-to identify clusters of high values (hot spots) and low values (cold spots).

RESULTS

Children in rural areas were much burdened with the occurrence of childhood morbidity. The study revealed positive spatial autocorrelation for childhood morbidity in Ghana. Childhood morbidity (diarrhoea, ARI, anaemia, and fever) clusters were identified within districts in the country. Children in rural areas were more likely to be morbid with diarrhoea, anaemia, and fever compared to those in urban areas. Hot spot districts for diarrhoea, anaemia and fever were mainly situated in semi-arid areas and those with ARI were located both at the semi-arid areas and coastal portions of Ghana.

CONCLUSION

Rural children are much exposed to have higher burden of a childhood morbidity compared to their urban counterparts. Most semi-arid districts in Ghana are burdened with diarrhoea, ARI, anaemia, and fever. To minimize the occurrence of childhood morbidity in Ghana, designing of more context-based interventions to target hot spots districts of these morbidities are required in order to use scarce resources judiciously.

Spatial, temporal, and spatiotemporal analysis of under-five diarrhea in Southern Ethiopia

Background

Despite improvements in prevention efforts, childhood diarrhea remains a public health concern. However, there may be substantial variation influenced by place, time, and season. Description of diarrheal clusters in time and space and understanding seasonal patterns can improve surveillance and management. The present study investigated the spatial and seasonal distribution and purely spatial, purely temporal, and space-time clusters of childhood diarrhea in Southern Ethiopia.

Methods

The study was a retrospective analysis of data from the Health Management Information System (HMIS) under-five diarrheal morbidity reports from July 2011 to June 2017 in Sidama Zone. Annual diarrhea incidence at district level was calculated. Incidence rate calculation and seasonal trend analysis were performed. The Kulldorff SaTScan software with a discrete Poisson model was used to identify statistically significant special, temporal, and space-time diarrhea clusters. ArcGIS 10.1 was used to plot the maps.

Results

A total of 202,406 under-five diarrheal cases with an annual case of 5822 per 100,000 under-five population were reported. An increasing trend of diarrhea incidence was observed over the 6 years with seasonal variation picking between February and May. The highest incidence rate (135.8/1000) was observed in the year 2016/17 in Boricha district. One statistically significant most likely spatial cluster (Boricha district) and six secondary clusters (Malga, Hulla, Aleta Wondo, Shebedino, Loka Abaya, Dale, and Wondogenet) were identified. One statistically significant temporal cluster (LLR = 2109.93, p < 0.001) during December 2013 to May 2015 was observed in all districts. Statistically significant spatiotemporal primary hotspot was observed in December 2012 to January 2015 in Malga district with a likelihood ratio of 1214.67 and a relative risk of 2.03. First, second, third, and fourth secondary hotspots occurred from January 2012 to May 2012 in Loka Abaya, December 2011 in Bursa, from March to April 2014 in Gorchie, and March 2012 in Wonsho districts.

Conclusion

Childhood diarrhea was not distributed randomly over space and time and showed an overall increasing trend of seasonal variation peaking between February and May. The health department and other stakeholders at various levels need to plan targeted interventional activities at hotspot seasons and areas to reduce morbidity and mortality.