This study investigated the spatial distribution, abundance, and infection rates of human schistosome-transmitting snails and related physicochemical parameters and environmental factors in 11 ...districts in KwaZulu-Natal (KZN) province, South Africa, from December 2020–February 2021. Snail sampling was carried out in 128 sites by two people for 15 min using scooping and handpicking methods. Geographical information system (GIS) was used to map surveyed sites. In situ measurements of physicochemical parameters were recorded, while remote sensing was used to obtain measurements for climatic factors required to achieve the study's objective. Cercarial shedding and snail-crushing methods were used to detect snail infections. Kruskal-Wallis test was used to test the differences in snail abundance among snail species, districts, and habitat types. A negative binomial generalized linear mixed model was used to identify the physicochemical parameters and environmental factors influencing the abundance of snail species. A total of 734 human schistosome-transmitting snails were collected. Bu. globosus were significantly more abundant (n = 488) and widely distributed (found in 27 sites) compared to B. pfeifferi (n = 246) found in 8 sites. Bu. globosus and B. pfeifferi had infection rates of 3.89% and 2.44%, respectively. Dissolved oxygen and normalized difference vegetation index showed a statistically positive relationship, while normalized difference wetness index showed a statistically negative relationship with the abundance of Bu. globosus. However, there was no statistically significant relationship between B. pfeifferi abundance, physicochemical parameters, and climatic factors. Our study described the current distribution, abundance, and infection status of human schistosome-transmitting snails in KZN province, which will contribute to informing control measure policies for schistosomiasis.
Occurrence of nutritional stress (due to depletion of fat reserves) in tsetse flies, associated with inadequate levels of access to blood meals, enhances susceptibility of the flies to trypanosome ...infection. Thus, in a tsetse-infested area, a spatial gradient of reducing tsetse habitat quality is potentially a gradient of increasing prospects for occurrence of stress in tsetse flies. This study investigated prevalence of trypanosome infection in
Glossina morsitans morsitans
and
G. pallidipes
along a transect line hypothesised to represent such a gradient, in relation to the edge of the tsetse belt and distribution of human settlements. This was undertaken in three sites located in Lundazi, Mpika and Rufunsa districts, respectively, in north-eastern Zambia. Human settlement was concentrated at the edge of the tsetse belt in the Mpika and Rufunsa sites and evenly distributed along transect line in the Lundazi site. Tsetse fly samples were collected using black-screen fly rounds and Epsilon traps. Detection of trypanosome infection was by dissection and microscopy in Lundazi and Mpika sites and loop-mediated isothermal amplification (LAMP) test in Rufunsa site. Multiple logistic regression models were applied to determine whether the following factors, ‘change in distance from edge of tsetse belt’, ‘tsetse sampling method’ and ‘sex of tsetse fly’, had effect on ‘prevalence of trypanosome infection’ in the tsetse flies. Only ‘increase in distance from the edge of tsetse belt’ for
G. m. morsitans
was significantly associated with ‘prevalence of trypanosome infection’ in the flies, in the Mpika and Rufunsa sites. Distance was associated with reduced likelihood of infection with ‘one or more subgenera of trypanosomes’ and with ‘Nannomonas trypanosomes’, in the case of ‘all sites collectively’, ‘Lundazi and Mpika sites collectively’, Mpika site alone, and Rufunsa site alone. Per site, increase in distance entailed reduced prospects for Trypanozoon infection but only in the Mpika and Rufunsa sites. We conclude that in the Mpika and Rufunsa sites, increase in distance from human settlements entailed reduced likelihood of trypanosome infection, likely due to reducing tsetse habitat degradation, increasing availability of hosts, and hence increasing levels of nutrition and fat reserves, thus enhancing tsetse immunity against trypanosome infection.
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•Focal nature of schistosomiasis was confirmed by the predicted hotspots.•The local semiparametric-GWR model performed better than the global model.•Socio-economic factors contribute ...to spatial variation of S. haematobium intensity.•The local coefficients and their significance levels varied across study area.
Schistosomiasis is a snail-transmitted parasitic disease endemic in most rural areas of sub-Saharan Africa. However, the currently used prediction models fail to capture the focal nature of its transmission due to the macro-geographical levels considered and paucity of data at local levels. This study determined the spatial distribution of Schistosoma haematobium and related risk factors in Ndumo area, uMkhanyakude District, KwaZulu-Natal province in South Africa. A sample of 435 schoolchildren between 10 to 15 years old from 10 primary schools was screened for S. haematobium using the filtration method. Getis-Ord Gi* and Bernoulli model were used to determine the hotspots of S. haematobium infection intensity based on their spatial distribution. Semiparametric-Geographically Weighted Regression (s-GWR) model was used to predict and analyse the spatial distribution of S. haematobium in relation to environmental and socio-economic factors. We confirmed that schistosomiasis transmission is focal in nature as indicated by significant S. haematobium cases and infection intensity clusters (p<0.05) in the study area. The s-GWR model performance was low (R2=0.45) and its residuals did not show autocorrelation (Moran’s I=−0.001; z-score=0.003 and p-value=0.997) indicating that the model was correctly spelled. The s-GWR model also indicated that the coefficients for some of the socio-economic variables such as distances of households from operational piped water collection points, distance from open water sources, religion, toilet use, household head and places of bath and laundry significantly (t-values+/−1.96) varied across the landscape thereby determining the variation of S. haematobium infection intensity. This evidence may be used for control and management of the disease at micro scale. However, there is need for further research into more factors that may improve the performance of the s-GWR models in determining the local variation of S. haematobium infection intensity.
Disease distribution is correlated to the distribution of the freshwater snails which in turn is influenced by the physicochemical status of the habitats. This study aimed to evaluate freshwater ...snail species diversity, abundance, and distribution in KwaZulu-Natal (KZN) province, South Africa, between December 2020 to February 2021. A total of 4576 freshwater snails consisting of 8 species were collected from 127 sites in 11 districts. Tarebia granifera snails were the most abundant (n = 2201), while bivalves (n = 95) were the least abundant. The highest and least Shannon–Weiner Simpson’s diversity indices were recorded in Ugu and iLembe districts, respectively. A negative relationship was observed between rainfall, Bulinus tropicus, Lymnaea natalensis, bivalves, and Physa acuta, while temperature had a positive relationship with B. globosus, B. pfeifferi, and T. granifera. A positive relationship was observed between B. globosus and B. pfeifferi (r = 0.713, p < 0.05). Snail presence constitutes potential health and economic risks to humans and animals in contact with the waterbody. Hence, our study described the current distribution, abundance, and species diversity of freshwater snails in the KZN province with insights into the possibilities of snail-based biological control for schistosomes intermediate host snails.
Floods are one of the most devastating weather‐related hazards that are affecting millions of people over the world every year. In some poor resource areas such as Mbire District in Zimbabwe, the ...floods are difficult to anticipate and prepare for. Hence the need for spatial modelling of the past flood events for effective response and management. This study modelled the flood extent and depth based on data from household surveys, transect walks and a digital elevation model (DEM). A sample of 304 households was used, with 70% for calibration and 30% for validation of the flood extent. Twenty‐four flood depth measurements obtained from transect walks were used to validate the modelled flood depths based on a linear regression model. The flood depth of the worst most recent flood (January 2015) at each household was combined with altitude from the DEM using the sum function, and the inverse distance weighting was applied to model the worst flood depth. The flood extent was considered as those areas where flood depth was higher than the DEM. Approximately 24% of the area was covered by floods. The modelled flood extent agreed reasonably well with what was reported during the survey (probability of detection 0.93 and accuracy level about 0.8). Most of the areas in the wards experienced flood depths greater than 2 m, especially along the major rivers. Such areas are dangerous for people, animals and properties such as boreholes, houses, schools and clinics located on the floodplain. These results can be used for planning purposes in preparing and responding to stages of the flood management cycle. However, there is a need for further research to improve the performance and applicability of the methodology applied in this study in other settings.
This study highlights the need and application of easy to use models in flood risk mapping especially in poor data or ungauged areas/basins for preparedness and response to floods. The model proposed in this study is based on data from household survey, transect walks and digital elevation model (DEM). The modelled flood extent agreed reasonably well with what was reported during the survey.
Despite its low cure rates and possible resistance, praziquantel (PZQ) is the only drug available for schistosomiasis treatment. Hence, monitoring its efficacy is crucial. This study assessed the ...efficacy of PZQ, determined re-infection and incidence rates of Schistosoma haematobium infection among school-going children in the Ndumo area, KwaZulu-Natal.
A cohort of 320 school-going children (10 - 15 years) in 10 primary schools was screened for S. haematobium infection using the filtration technique. Infected children were treated at different times and hence were divided into two sub-cohorts; A1 and A2. Non-infected children constituted the sub-cohort B. Children who continued excreting viable eggs 4 weeks post-treatment received a second dose of PZQ. Re-infection rates were determined in sub-cohort A1 and A2 at 28 and 20 weeks post-treatment, respectively. Cure rates (CR) and egg reduction rates (ERR) were calculated. Incidence rate was assessed 28 weeks post baseline survey using children that were negative for schistosome eggs at that survey. Analysis of data was done using the Chi square and the Wilcoxon rank test. A 95% confidence interval with a P-value < 0.05 determined significance.
At baseline, 120 (37.5%) of the 320 study participants were found infected with Schistosoma haematobium. Heavy infections accounted for 36.7%. The calculated cure rates were 88.07% and 82.92% for females and males, respectively. Egg Reduction Rates of 80% and 64% for females and males were observed 4 weeks after the initial treatment. After the second treatment, CR was 100% in females and 50% in males with an ERR of 100% in females and 70% in males. At 20 and 28 weeks post treatment, reinfection rates of 8.03% and 8.00% were observed, respectively, giving an overall rate of 8.1%. An incidence rate of 4.1% was observed 28 weeks after the baseline screening.
The study indicated high CR while the ERR was low suggesting a reduced PZQ efficacy. The efficacy improved among females after the second dose. Re-infection rates at 20 and 28 weeks post-treatment were low. The study also indicated a low incidence rate for the 28 weeks period.
Primary health care facilities are at the forefront of helping communities affected by natural disasters. However, such facilities are also vulnerable to the effects of extreme weather events ...triggered by climate change. The April 2022 floods in the south-eastern region of South Africa claimed the lives of over 400 people, the loss of 16 000 houses and resulted in major damage to infrastructure. Most damage was localised in the eThekwini area in KwaZulu-Natal, which is the country's third most populous city. This report describes the impact of the floods on primary health care facilities in eThekwini and their preparedness for extreme weather events.Contribution: Extreme weather events induced by climate change highlight the need for primary health care facilities to develop disaster management strategies that consider climate change.
During the last 30 years, the development of geographical information systems and satellites for Earth observation has made important progress in the monitoring of the weather, climate, environmental ...and anthropogenic factors that influence the reduction or the reemergence of vector-borne diseases. Analyses resulting from the combination of geographical information systems (GIS) and remote sensing have improved knowledge of climatic, environmental, and biodiversity factors influencing vector-borne diseases (VBDs) such as malaria, visceral leishmaniasis, dengue, Rift Valley fever, schistosomiasis, Chagas disease and leptospirosis. These knowledge and products developed using remotely sensed data helped and continue to help decision makers to better allocate limited resources in the fight against VBDs.
Because VBDs are linked to climate and environment, we present here our experience during the last four years working with the projects under the, World Health Organization (WHO)/ The Special Programme for Research and Training in Tropical Diseases (TDR)-International Development Research Centre (IDRC) Research Initiative on VBDs and Climate Change to integrate climate and environmental information into research and decision-making processes. The following sections present the methodology we have developed, which uses remote sensing to monitor climate variability, environmental conditions, and their impacts on the dynamics of infectious diseases. We then show how remotely sensed data can be accessed and evaluated and how they can be integrated into research and decision-making processes for mapping risks, and creating Early Warning Systems, using two examples from the WHO TDR projects based on schistosomiasis analysis in South Africa and Trypanosomiasis in Tanzania.
The tools presented in this article have been successfully used by the projects under the WHO/TDR-IDRC Research Initiative on VBDs and Climate Change. Combined with capacity building, they are an important piece of work which can significantly contribute to the goals of WHO Global Vector Control Response and to the Sustainable Development Goals especially those on health and climate action.
Although there has been a decline in the number of malaria cases in Zimbabwe since 2010, the disease remains the biggest public health threat in the country. Gwanda district, located in Matabeleland ...South Province of Zimbabwe has progressed to the malaria pre-elimination phase. The aim of this study was to determine the spatial distribution of malaria incidence at ward level for improving the planning and implementation of malaria elimination in the district.
The Poisson purely spatial model was used to detect malaria clusters and their properties, including relative risk and significance levels at ward level. The geographically weighted Poisson regression (GWPR) model was used to explore the potential role and significance of environmental variables rainfall, minimum and maximum temperature, altitude, Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), rural/urban and malaria control strategies indoor residual spraying (IRS) and long-lasting insecticide-treated nets (LLINs) on the spatial patterns of malaria incidence at ward level.
Two significant clusters (p < 0.05) of malaria cases were identified: (1) ward 24 south of Gwanda district and (2) ward 9 in the urban municipality, with relative risks of 5.583 and 4.316, respectively. The semiparametric-GWPR model with both local and global variables had higher performance based on AICc (70.882) compared to global regression (74.390) and GWPR which assumed that all variables varied locally (73.364). The semiparametric-GWPR captured the spatially non-stationary relationship between malaria cases and minimum temperature, NDVI, NDWI, and altitude at the ward level. The influence of LLINs, IRS and rural or urban did not vary and remained in the model as global terms. NDWI (positive coefficients) and NDVI (range from negative to positive coefficients) showed significant association with malaria cases in some of the wards. The IRS had a protection effect on malaria incidence as expected.
Malaria incidence is heterogeneous even in low-transmission zones including those in pre-elimination phase. The relationship between malaria cases and NDWI, NDVI, altitude, and minimum temperature may vary at local level. The results of this study can be used in planning and implementation of malaria control strategies at district and ward levels.
The World Health Organization (WHO) recom‑ mends same‑day initiation (SDI) of antiretroviral therapy (ART) for all individuals diagnosed with HIV irrespective of CD4+ count or clinical stage. ...Implementation of program is still far from reaching its goals. This study assessed the level of implementation of same day ART initiation. A longitudinal study was conducted at four primary healthcare clinics in eThekwini municipality KwaZulu‑Natal. Data was collected between June 2020 to October 2020 using a data extrac‑ tion form. Data on individuals tested HIV positive, number of SDI of ART; and clinicians working on UTT program were compiled from clinic registers, and Three Interlinked Electronic Registers.Net (TIER.Net). Non‑governmental organisations (NGO) supporting the facility and services information was collected. Among the 403 individuals who tested HIV positive, 279 (69.2%) were initiated on ART on the same day of HIV diagnosis from the four facilities. There was a significant association between health facility and number of HIV positive individuals initiated on SDI (chi‑square=10.59; P‑value=0.008). There was a significant association between facilities with support from all NGOs and ART SDI (chi‑square=10.18; P‑value=0.015. There was a significant association between staff provision in a facility and SDI (chi‑square=7.51; P‑value=0.006). Urban areas clinics were more likely to have high uptake of SDI compared to rural clinics (chi‑square=11,29; P‑value=0.003). Implementation of the Universal Test and Treat program varies by facility indi‑ cating the need for the government to monitor and standardize implementation of the policy if the program is to yield success.
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