A Neighbor-Based Approach to Identify Tuberculosis Exposure, the Kopanyo Study.

Contact investigation is one public health measure used to prevent tuberculosis by identifying and treating persons exposed to Mycobacterium tuberculosis. Contact investigations are a major tenet of global tuberculosis elimination efforts, but for many reasons remain ineffective. We describe a novel neighbor-based approach to reframe contact investigations.

Molecular, Spatial, and Field Epidemiology Suggesting TB Transmission in Community, Not Hospital, Gaborone, Botswana.

During 2012-2015, 10 of 24 patients infected with matching genotypes of Mycobacterium tuberculosis received care at the same hospital in Gaborone, Botswana. Nosocomial transmission was initially suspected, but we discovered plausible sites of community transmission for 20 (95%) of 21 interviewed patients. Active case-finding at these sites could halt ongoing transmission.

Tuberculosis attributed to transmission within healthcare facilities, Botswana-The Kopanyo Study.

OBJECTIVE: Healthcare facilities are a well-known high-risk environment for transmission of M. tuberculosis, the etiologic agent of tuberculosis (TB) disease. However, the link between M. tuberculosis transmission in healthcare facilities and its role in the general TB epidemic is unknown. We estimated the proportion of overall TB transmission in the general population attributable to healthcare facilities. METHODS: We combined data from a prospective, population-based molecular epidemiologic study with a universal electronic medical record (EMR) covering all healthcare facilities in Botswana to identify biologically plausible transmission events occurring at the healthcare facility. Patients with M. tuberculosis isolates of the same genotype visiting the same facility concurrently were considered an overlapping event. We then used TB diagnosis and treatment data to categorize overlapping events into biologically plausible definitions. We calculated the proportion of overall TB cases in the cohort that could be attributable to healthcare facilities. RESULTS: In total, 1,881 participants had TB genotypic and EMR data suitable for analysis, resulting in 46,853 clinical encounters at 338 healthcare facilities. We identified 326 unique overlapping events involving 370 individual patients; 91 (5%) had biologic plausibility for transmission occurring at a healthcare facility. A sensitivity analysis estimated that 3%-8% of transmission may be attributable to healthcare facilities. CONCLUSIONS: Although effective interventions are critical in reducing individual risk for healthcare workers and patients at healthcare facilities, our findings suggest that development of targeted interventions aimed at community transmission may have a larger impact in reducing TB.

Applying the Haddon matrix conceptual model to guide motor vehicle crash injury research and prevention in Botswana.

INTRODUCTION: Little literature addresses the burden of injury in Botswana, including trauma from motor-vehicle crashes (MVCs). In response, the University of Botswana and the Botswana Ministry of Health and Wellness are collaborating with the University of Pennsylvania to enhance injury and trauma research capacity in Botswana. Here we describe this training program and a research exercise to identify opportunities to prevent, through future research and countermeasures, MVCs specifically in Botswana. METHODS: We initiated a mixed-methods study during a training module during the first two years of the program. The module introduced the Haddon matrix as a conceptual framework, and asked trainees to identify host, vector, and physical/social environment risk factors for MVCs that, if targeted, may lead to primary, secondary, or tertiary prevention. We conducted 10 photovoice elicitation interviews; results were thematically analyzed to further elucidate the context of MVCs in Botswana and potential countermeasures. RESULTS: Our process identified a range of ideas as barriers or facilitators to MVC prevention. The most commonly cited barriers were animals on the road, drunk or reckless driving, poor road quality, lack of road signs/traffic signals to orient drivers, and poor visibility (e.g., no street lighting; poor lighting on vehicles). Regarding primary prevention, participants identified features prior to the crash, across all matrix levels, as influencers of crashes in Botswana. Among these, several human factors (i.e., over-speeding; drunk driving) and environmental factors (i.e., livestock on road) were commonly mentioned as contributors to MVCs, as were cattle gates and traffic calming measures for prevention. CONCLUSION: Results of the Haddon matrix exercise proved useful for training burgeoning Batswana researchers to think conceptually about the occurrence of MVCs in Botswana and think creatively about targeting countermeasures for prevention. The exercise resulted in potential research questions for the trainees to pursue in mentored research of their own.

Undetected tuberculosis at enrollment and after hospitalization in medical and oncology wards in Botswana.

Cancer patients are at higher risk of tuberculosis (TB) infection, especially in hospital settings with high TB/HIV burden. The study was implemented among adult patients admitted to the largest tertiary-level referral hospital in Botswana. We estimated the TB prevalence at admission and the rate of newly diagnosed TB after hospitalization in the medical and oncology wards, separately. Presumptive TB cases were identified at admission through symptom screening and underwent the diagnostic evaluation through GeneXpert. Patients with no evidence of TB were followed-up until TB diagnosis or the end of the study. In the medical and oncology wards, four of 867 admitted patients and two of 240 had laboratory-confirmed TB at admission (prevalence = 461.4 and 833.3 per 100,000, respectively.) The post-admission TB rate from the medical wards was 28.3 cases per 1,000 person-year during 424.5 follow-up years (post-admission TB rate among HIV-positive versus. -negative = 54.1 and 9.8 per 1,000 person-year, respectively [Rate Ratio = 5.5]). No post-admission TB case was detected from the oncology ward. High rates of undetected TB at admission at both medical and oncology wards, and high rate of newly diagnosed TB after admission at medical wards suggest that TB screening and diagnostic evaluation should target all patients admitted to a hospital in high-burden settings.