Spatial Heterogeneity Association of HIV Incidence with Socio-economic Factors in Zimbabwe

This study examined the spatial heterogeneity association of HIV incidence and socio-economic factors including poverty severity index,permanently employed females and males,unemployed females,percentage of poor households i.e.,poverty prevalence,night lights index,literacy rate,household food security,and Gini index at district level in Zimbabwe.A mix of spatial analysis methods including Poisson model based on original log likelihood ratios(LLR),global Moran’s I,local indicator of spatial association-LISA were employed to determine the HIV hotspots.Geographically Weighted Poisson Regression(GWPR)and semi-parametric GWPR(s-GWPR)were used to determine the spatial association between HIV incidence and socio-economic factors.HIV incidence(number of cases per 1000)ranged from 0.6(Buhera district)to 13.30(Mangwe district).Spatial clustering of HIV incidence was observed(Global Moran’s I=-0.150;Z score 3.038;p-value 0.002).Significant clusters of HIV were observed at district level.HIV incidence and its association with socio-economic factors varied across the districts except percentage of females unemployed.Intervention programmes to reduce HIV incidence should address the identified socio-economic factors at district level.

Efficacy of praziquantel on Schistosoma haematobium and re-infection rates among school-going children in the Ndumo area of uMkhanyakude district,KwaZulu-Natal,South Africa

Background: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.Methods: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.Results: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.Conclusions: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 posttreatment were low.The study also indicated a low incidence rate for the 28 weeks period.

Data and tools to integrate climate and environmental information into public health

Background: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.Main body: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.Conclusions:The tools presented in this article have been successfully used by the projects under the WHO/TDRIDRC 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.