Natashia Morris

Use of Google Earth to strengthen public health capacity and facilitate management of vector-borne diseases in resource-poor environments.

OBJECTIVE Novel, inexpensive solutions are needed for improved management of vector-borne and other diseases in resource-poor environments. Emerging free software providing access to satellite imagery and simple editing tools (e.g. Google Earth) complement existing geographic information system (GIS) software and provide new opportunities for: (i) strengthening overall public health capacity through development of information for city infrastructures; and (ii) display of public health data directly on an image of the physical environment. METHODS We used freely accessible satellite imagery and a set of feature-making tools included in the software (allowing for production of polygons, lines and points) to generate information for city infrastructure and to display disease data in a dengue decision support system (DDSS) framework. FINDINGS Two cities in Mexico (Chetumal and Merida) were used to demonstrate that a basic representation of city infrastructure useful as a spatial backbone in a DDSS can be rapidly developed at minimal cost. Data layers generated included labelled polygons representing city blocks, lines representing streets, and points showing the locations of schools and health clinics. City blocks were colour-coded to show presence of dengue cases. The data layers were successfully imported in a format known as shapefile into a GIS software. CONCLUSION The combination of Google Earth and free GIS software (e.g. HealthMapper, developed by WHO, and SIGEpi, developed by PAHO) has tremendous potential to strengthen overall public health capacity and facilitate decision support system approaches to prevention and control of vector-borne diseases in resource-poor environments.

Transmission of Extensively Drug-Resistant Tuberculosis in South Africa.

BACKGROUND Drug‐resistant tuberculosis threatens recent gains in the treatment of tuberculosis and human immunodeficiency virus (HIV) infection worldwide. A widespread epidemic of extensively drug‐resistant (XDR) tuberculosis is occurring in South Africa, where cases have increased substantially since 2002. The factors driving this rapid increase have not been fully elucidated, but such knowledge is needed to guide public health interventions. METHODS We conducted a prospective study involving 404 participants in KwaZulu‐Natal Province, South Africa, with a diagnosis of XDR tuberculosis between 2011 and 2014. Interviews and medical‐record reviews were used to elicit information on the participants’ history of tuberculosis and HIV infection, hospitalizations, and social networks. Mycobacterium tuberculosis isolates underwent insertion sequence (IS)6110 restriction‐fragment–length polymorphism analysis, targeted gene sequencing, and whole‐genome sequencing. We used clinical and genotypic case definitions to calculate the proportion of cases of XDR tuberculosis that were due to inadequate treatment of multidrug‐resistant (MDR) tuberculosis (i.e., acquired resistance) versus those that were due to transmission (i.e., transmitted resistance). We used social‐network analysis to identify community and hospital locations of transmission. RESULTS Of the 404 participants, 311 (77%) had HIV infection; the median CD4+ count was 340 cells per cubic millimeter (interquartile range, 117 to 431). A total of 280 participants (69%) had never received treatment for MDR tuberculosis. Genotypic analysis in 386 participants revealed that 323 (84%) belonged to 1 of 31 clusters. Clusters ranged from 2 to 14 participants, except for 1 large cluster of 212 participants (55%) with a LAM4/KZN strain. Person‐to‐person or hospital‐based epidemiologic links were identified in 123 of 404 participants (30%). CONCLUSIONS The majority of cases of XDR tuberculosis in KwaZulu‐Natal, South Africa, an area with a high tuberculosis burden, were probably due to transmission rather than to inadequate treatment of MDR tuberculosis. These data suggest that control of the epidemic of drug‐resistant tuberculosis requires an increased focus on interrupting transmission. (Funded by the National Institute of Allergy and Infectious Diseases and others.)

The feasibility of malaria elimination in South Africa

BackgroundFollowing the last major malaria epidemic in 2000, malaria incidence in South Africa has declined markedly. The decrease has been so emphatic that South Africa now meets the World Health Organization (WHO) threshold for malaria elimination. Given the Millennium Development Goal of reversing the spread of malaria by 2015, South Africa is being urged to adopt an elimination agenda. This study aimed to determine the appropriateness of implementing a malaria elimination programme in present day South Africa.MethodsAn assessment of the progress made by South Africa in terms of implementing an integrated malaria control programme across the three malaria-endemic provinces was undertaken. Vector control and case management data were analysed from the period of 2000 until 2011.ResultsBoth malaria-related morbidity and mortality have decreased significantly across all three malaria-endemic provinces since 2000. The greatest decline was seen in KwaZulu-Natal where cases decreased from 42,276 in 2000 to 380 in 2010 and deaths dropped from 122 in 2000 to six in 2010. Although there has been a 49.2 % (8,553 vs 4,214) decrease in the malaria cases reported in Limpopo Province, currently it is the largest contributor to the malaria incidence in South Africa. Despite all three provinces reporting average insecticide spray coverage of over 80%, malaria incidence in both Mpumalanga and Limpopo remains above the elimination threshold. Locally transmitted case numbers have declined in all three malaria provinces but imported case numbers have been increasing. Knowledge gaps in vector distribution, insecticide resistance status and drug usage were also identified.ConclusionsMalaria elimination in South Africa is a realistic possibility if certain criteria are met. Firstly, there must be continued support for the existing malaria control programmes to ensure the gains made are sustained. Secondly, cross border malaria control initiatives with neighbouring countries must be strongly encouraged and supported to reduce malaria in the region and the importation of malaria into South Africa. Thirdly, operational research, particularly on vector distribution and insecticide resistance status must be conducted as a matter of urgency, and finally, the surveillance systems must be refined to ensure the information required to inform an elimination agenda are routinely collected.

Towards malaria elimination in the MOSASWA (Mozambique, South Africa and Swaziland) region

The substantial impact of cross-border collaborative control efforts on the burden of malaria in southern Africa has previously been demonstrated through the successes of the Lubombo Spatial Development Initiative. Increases in malaria cases recorded in the three partner countries (Mozambique, South Africa, Swaziland) since termination of that programme in 2011 have provided impetus for the resuscitation of cooperation in the form of the MOSASWA malaria initiative. MOSASWA, launched in 2015, seeks to renew regional efforts to accelerate progress towards malaria elimination goals already established in the region. National malaria programmes, together with developmental partners, academic institutions and the private sector seek to harmonize policy, strengthen capacity, share expertise, expand access to elimination interventions particularly amongst migrant and border population groups, mobilize resources and advocate for long-term funding to ultimately achieve and sustain malaria elimination in the MOSASWA region.

Mapping indicators of sexually transmitted infection services in the South African public health sector

Background  Prevention and early treatment of sexually transmitted infections (STIs) is a high public health priority in South Africa. In 2002 a national survey of public health care (PHC) facilities was conducted to develop measurable indicators for monitoring and evaluation of the National STI programme. In this paper we present maps of key indicators obtained from the survey, and discuss their programmatic implications. We also address some methodological issues that arise in the context of producing appropriate maps.

Spatial distribution of extensively drug-resistant tuberculosis (XDR TB) patients in KwaZulu-Natal, South Africa.

Background KwaZulu-Natal province, South Africa, has among the highest burden of XDR TB worldwide with the majority of cases occurring due to transmission. Poor access to health facilities can be a barrier to timely diagnosis and treatment of TB, which can contribute to ongoing transmission. We sought to determine the geographic distribution of XDR TB patients and proximity to health facilities in KwaZulu-Natal. Methods We recruited adults and children with XDR TB diagnosed in KwaZulu-Natal. We calculated distance and time from participants’ home to the closest hospital or clinic, as well as to the actual facility that diagnosed XDR TB, using tools within ArcGIS Network analyst. Speed of travel was assigned to road classes based on Department of Transport regulations. Results were compared to guidelines for the provision of social facilities in South Africa: 5km to a clinic and 30km to a hospital. Results During 2011–2014, 1027 new XDR TB cases were diagnosed throughout all 11 districts of KwaZulu-Natal, of whom 404 (39%) were enrolled and had geospatial data collected. Participants would have had to travel a mean distance of 2.9 km (CI 95%: 1.8–4.1) to the nearest clinic and 17.6 km (CI 95%: 11.4–23.8) to the nearest hospital. Actual distances that participants travelled to the health facility that diagnosed XDR TB ranged from <10 km (n = 143, 36%) to >50 km (n = 109, 27%), with a mean of 69 km. The majority (77%) of participants travelled farther than the recommended distance to a clinic (5 km) and 39% travelled farther than the recommended distance to a hospital (30 km). Nearly half (46%) of participants were diagnosed at a health facility in eThekwini district, of whom, 36% resided outside the Durban metropolitan area. Conclusions XDR TB cases are widely distributed throughout KwaZulu-Natal province with a denser focus in eThekwini district. Patients travelled long distances to the health facility where they were diagnosed with XDR TB, suggesting a potential role for migration or transportation in the XDR TB epidemic.