Background: To optimally allocate limited health resources in responding to the HIV epidemic, South Africa has undertaken to generate local epidemiological profiles identifying high disease burden areas. Central to achieving this, is the need for readily available quality health data linked to both large and small geographic areas. South Africa has relied on national population-based surveys: the Household HIV Survey and the National Antenatal Sentinel HIV and Syphilis Prevalence Survey (ANC) amongst others for such data for informing policy decisions. However, these surveys are conducted approximately every 2 and 3 years creating a gap in data and evidence required for policy. At subnational levels, timely decisions are required with frequent course corrections in the interim. Routinely collected HIV testing data at public health facilities have the potential to provide this much needed information, as a proxy measure of HIV prevalence in the population, when survey data is not available. The South African District health information system (DHIS) contains aggregated routine health data from public health facilities which is used in this article.Methods: Using spatial interpolation methods we combine three “types” of data: (1) 2015 gridded high-resolution population data, (2) age-structure data as defined in South Africa mid-year population estimates, 2015; and (3) georeferenced health facilities HIV-testing data from DHIS for individuals (15–49 years old) who tested in health care facilities in the district in 2015 to delineate high HIV disease burden areas using density surface of either HIV positivity and/or number of people living with HIV (PLHIV). For validation, we extracted interpolated values at the facility locations and compared with the real observed values calculating the residuals. Lower residuals means the Inverse Weighted Distance (IDW) interpolator provided reliable prediction at unknown locations. Results were adjusted to provincial published HIV estimates and aggregated to municipalities. Uncertainty measures map at municipalities is provided. Data on major cities and roads networks was only included for orientation and better visualization of the high burden areas.Results: Results shows the HIV burden at local municipality level, with high disease burden in municipalities in eThekwini, iLembe and uMngundgudlovu; and around major cities and national routes.Conclusion: The methods provide accurate estimates of the local HIV burden at the municipality level. Areas with high population density have high numbers of PLHIV. The analysis puts into the hand of decision makers a tool that they can use to generate evidence for HIV programming. The method allows decision makers to routinely update and use facility level data in understanding the local epidemic.

Micro-enterprises (MEs) have been shown to collectively be the largest employer in most developing countries thus playing a significant role in the countries economies. Using informal sector micro-enterprise furniture makers (wood and metal) in Nairobi, Kenya and based on Porter's competitive business strategies typology, this study sought to determine if the strategies employed by the informal sector MEs fit within the typology framework, and if membership within the strategic groups in the typology are a predictor of better business business performance. From the study, although membership within the two focus strategic groups of differentiation and low cost was confirmed, unlike studies done with medium and large enterprises, membership was not found to be a predictor of better business performance. Porter's typology may therefore not adequately capture the competitive business activities relevant to and directly by MEs, presenting an opportunity for research into the development of competitive business strategy typologies directly derived from their activities and therefore applicable to them.

Approximately 5% of all emergency department (ED) visits require evaluation of chest pain and atypical symptoms for diagnosis or exclusion of myocardial infarction or acute coronary syndrome (ACS) (P. Rui, K. Kang, & J. J. Ashman, 2016). Health care providers rely on effective tests and assessment protocols for definitive diagnosis of ACS. Cardiac biomarkers in troponin T assays enable rapid exclusion of ACS. This project compared high-sensitivity troponin T assay to conventional troponin T assay in reducing unnecessary stress tests for ACS exclusion, length of stay in the ED, and rate of readmissions within 30 days after ACS exclusion and discharge. A retrospective review of 300 medical records for exclusion of ACS compared 150 patients receiving conventional troponin T assay and 150 patients receiving high-sensitivity troponin T assay. The mean length of stay in the preintervention group was 8.3 hr (SD = 1.60) compared with 3.9 hr (SD = 1.56) in the postintervention group (t (298) = 24.56, p < 0.001). A significant difference was found in necessary and unnecessary stress testing (X 2 (1) =17.42, p < 0.05). The preintervention group had significantly more normal stress tests and the postintervention group had significantly more abnormal stress tests. In the preintervention group, 4 (2.7%) patients were readmitted within 30 days with ACS; no readmissions were reported for the postintervention group. Findings supported outcome improvements with the high-sensitivity troponin T assay. Using high-sensitivity troponin T assay in the diagnosis protocol can improve length of stay for patients with exclusion of ACS and reduce unnecessary stress tests during the ED stay.