The Role of Spatial Statistics in the Control and Elimination of Neglected Tropical Diseases in Sub-Saharan Africa

Stanton, Michelle C.

doi:10.1016/bs.apar.2017.01.001

Cited by 7 publications

(5 citation statements)

References 175 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The kriging method is widely used for predicting spatial patterns (e.g. the prevalence or intensity of infection) at non-sampling locations [25–29]. Kriging involves including a fixed number of nearest neighbour points within a fixed radius [26] and relies on semi-variograms that quantify spatial autocorrelation among all pairs of data according to distance [30].…”

Section: Methodsmentioning

confidence: 99%

Parasitic infections in relation to practices and knowledge in a rural village in Northern Thailand with emphasis on fish-borne trematode infection

et al. 2018

View full text Add to dashboard Cite

The present study integrates several aspects of a parasitological survey in a rural community village combining community knowledge of parasites, their potential transmission routes and health risk factors. A rural community located in Northern Thailand was surveyed for intestinal parasites, and an overall prevalence of 45.2% for helminths and 4.8% for protozoan infections was identified. Socio-demographic characteristics, customs and perceptions were compiled using individual questionnaires and interviews for participants surveyed for parasitic screening. The results allowed us to determine the knowledge and perception of local people concerning helminthic infection and transmission. Despite the fact that the participants in this community were aware of parasitic transmission routes, their widespread custom of eating raw fish and meat render the reduction of helminthiasis difficult. A detailed study on the infection of fish-borne parasitic trematodes, the most prevalent helminth, allowed us to determine that the distance from a given household to the river is a determinant of infection intensity. Health education activities organised in the local community resulted in a change in perception of risks associated with parasite transmission.

show abstract

Section: Methodsmentioning

confidence: 99%

Parasitic infections in relation to practices and knowledge in a rural village in Northern Thailand with emphasis on fish-borne trematode infection

et al. 2018

View full text Add to dashboard Cite

show abstract

“…The importance of more accurate information on spatial heterogeneous distribution of disease and endemicity level at sub-district or village level is recognized by program managers of neglected tropical diseases as an added value to determine the target populations for preventive interventions [ 36 , 37 ]. For example, schistosomiasis and soil-transmitted helminths show a heterogeneous distribution with large clusters of cases located near infested water and soil, respectively.…”

Section: Discussionmentioning

confidence: 99%

Determining target populations for leprosy prophylactic interventions: a hotspot analysis in Indonesia

et al. 2022

View full text Add to dashboard Cite

Background Leprosy incidence remained at around 200,000 new cases globally for the last decade. Current strategies to reduce the number of new patients include early detection and providing post-exposure prophylaxis (PEP) to at-risk populations. Because leprosy is distributed unevenly, it is crucial to identify high-risk clusters of leprosy cases for targeting interventions. Geographic Information Systems (GIS) methodology can be used to optimize leprosy control activities by identifying clustering of leprosy cases and determining optimal target populations for PEP. Methods The geolocations of leprosy cases registered from 2014 to 2018 in Pasuruan and Pamekasan (Indonesia) were collected and tested for spatial autocorrelation with the Moran’s I statistic. We did a hotspot analysis using the Heatmap tool of QGIS to identify clusters of leprosy cases in both areas. Fifteen cluster settings were compared, varying the heatmap radius (i.e., 500 m, 1000 m, 1500 m, 2000 m, or 2500 m) and the density of clustering (low, moderate, and high). For each cluster setting, we calculated the number of cases in clusters, the size of the cluster (km2), and the total population targeted for PEP under various strategies. Results The distribution of cases was more focused in Pasuruan (Moran’s I = 0.44) than in Pamekasan (0.27). The proportion of total cases within identified clusters increased with heatmap radius and ranged from 3% to almost 100% in both areas. The proportion of the population in clusters targeted for PEP decreased with heatmap radius from > 100% to 5% in high and from 88 to 3% in moderate and low density clusters. We have developed an example of a practical guideline to determine optimal cluster settings based on a given PEP strategy, distribution of cases, resources available, and proportion of population targeted for PEP. Conclusion Policy and operational decisions related to leprosy control programs can be guided by a hotspot analysis which aid in identifying high-risk clusters and estimating the number of people targeted for prophylactic interventions.

show abstract

“…Recent technical advances in the field of geospatial epidemiology have provided new strategies that can support BU surveillance 64 . Although the transmission of BU in Africa remains unclear, the environmental dependence of Mycobacterium ulcerans bacteria make both pathogen and disease amenable to geospatial models that predict disease occurence 1 .…”

Section: Improved Targeting and Evaluation Of Surveillancementioning

confidence: 99%

Methods and Approaches for Buruli Ulcer Surveillance in Africa: Lessons Learnt and Future Directions

Timothy

Pullan

Yotsu

2021

Methods in Molecular Biology

View full text Add to dashboard Cite

Over 95% of the global burden of Buruli ulcer disease (BU) caused by Mycobacterium ulcerans occurs in equatorial Africa. National and sub-national programmes have implemented various approaches to improve detection and reporting of incident cases over recent decades.Regional incidence rates are currently in decline, however, surveillance targets outlined in 2012 by WHO have been missed and detection bias may contribute to these trends. In light of the new 2030 NTD roadmap and disease-specific targets, BU programmes are required to strengthen case detection and begin a transition towards integration with other skin-NTDs. This transition comes with new opportunities to enhance existing BU surveillance systems and develop novel approaches for implementation and evaluationIn this review, we present a breakdown and assessment of the methods and approaches that have been the pillars of BU surveillance systems in Africa i) Passive case detection ii) Data systems iii) Clinical training iv) Active case finding v) Burden estimation vi) Laboratory confirmation pathways. We discuss successes, challenges and relevant cases studies before highlighting opportunities for future development and evaluation including i) Novel data collection tools ii) Risk-based surveillance iii) Integrated skin-NTD surveillance. We draw on both experience and available literature to critically evaluate methods of BU surveillance in Africa and highlight new approaches to help achieve 2030 roadmap targets.

show abstract

The Role of Spatial Statistics in the Control and Elimination of Neglected Tropical Diseases in Sub-Saharan Africa

Cited by 7 publications

References 175 publications

Parasitic infections in relation to practices and knowledge in a rural village in Northern Thailand with emphasis on fish-borne trematode infection

Parasitic infections in relation to practices and knowledge in a rural village in Northern Thailand with emphasis on fish-borne trematode infection

Determining target populations for leprosy prophylactic interventions: a hotspot analysis in Indonesia

Methods and Approaches for Buruli Ulcer Surveillance in Africa: Lessons Learnt and Future Directions

Contact Info

Product

Resources

About