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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.

What is already known about this topic? A novel HIV infection surveillance initiative was implemented in Malawi to collect data on recent HIV infections among new diagnoses to characterize the epidemic and guide the public health response. What is added by this report? Higher proportions of recent infections were identified among females, persons aged

IntroductionCombining genomic and geospatial data can be useful for understanding Mycobacterium tuberculosis (Mtb) transmission in high tuberculosis burden settings.MethodsWe performed whole genome sequencing (WGS) on Mtb DNA extracted from sputum cultures from a population-based tuberculosis study conducted in 2012–2016 in Gaborone, Botswana. We used kernel density estimation, spatial K-functions, and created spatial distributions of phylogenetic trees. WGS-based clusters of isolates ≤5 single nucleotide polymorphisms were considered recent transmission, and large WGS-based clusters (≥10 members) were considered outbreaks.ResultsWe analyzed data from 1449 participants with culture-confirmed TB. Among these, 946 (65%) participants had both molecular and geospatial data. A total of 62 belonged to five large outbreaks (10–19 participants each). Geospatial clustering was detected in two of the five large outbreaks, suggesting heterogeneous spatial patterns within the community.ConclusionsIntegration of genomic and geospatial data identified distinct patterns of tuberculosis transmission in a high-tuberculosis burden setting. Targeted interventions in these smaller geographies may interrupt on-going transmission.

Tuberculosis (TB) elimination requires interrupting transmission of Mycobacterium tuberculosis. We used a multidisciplinary approach to describe TB transmission in 2 sociodemographically distinct districts in Botswana (Kopanyo Study). During August 2012–March 2016, all patients who had TB were enrolled, their sputum samples were cultured, and M. tuberculosis isolates were genotyped by using 24-locus mycobacterial interspersed repetitive units–variable number of tandem repeats. Of 5,515 TB patients, 4,331 (79%) were enrolled. Annualized TB incidence varied by geography (range 66–1,140 TB patients/100,000 persons). A total of 1,796 patient isolates had valid genotyping results and residential geocoordinates; 780 (41%) patients were involved in a localized TB transmission event. Residence in areas with a high burden of TB, age

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.

Mycobacterium tuberculosis transmission dynamics in high-burden settings are poorly understood. Growing evidence suggests transmission may be characterized by extensive individual heterogeneity in secondary cases (i.e., superspreading), yet the degree and influence of such heterogeneity is largely unknown and unmeasured in high burden-settings. We conducted a prospective, population-based molecular epidemiology study of TB transmission in both an urban and rural setting of Botswana, one of the highest TB burden countries in the world. We used these empirical data to fit two mathematical models (urban and rural) that jointly quantified both the effective reproductive number, [Formula: see text], and the propensity for superspreading in each population. We found both urban and rural populations were characterized by a high degree of individual heterogeneity, however such heterogeneity disproportionately impacted the rural population: 99% of secondary transmission was attributed to only 19% of infectious cases in the rural population compared to 60% in the urban population and the median number of incident cases until the first outbreak of 30 cases was only 32 for the rural model compared to 791 in the urban model. These findings suggest individual heterogeneity plays a critical role shaping local TB epidemiology within subpopulations.

Background Mineworkers in Southern Africa have the highest rates of tuberculosis (TB) among working populations in the world (The World Bank, Benefits and costs associated with reducing tuberculosis among Southern Africa’s mineworkers, 2014), making mineworkers a key population for TB program efforts. The current evaluation aimed to characterize mineworkers and former (ex-) mineworkers, and assess knowledge, attitudes and practices related to TB and HIV care among mineworkers and healthcare workers (HCWs) in Zambia. Methods A mixed-methods evaluation of current and former (ex-) mineworkers and HCWs was conducted in the Copperbelt and North-Western provinces, Zambia. Knowledge, attitudes and practices (KAPs) related to TB care and policies were assessed using a structured survey. Focus Group Discussions (FGDs) were conducted with current and ex-mineworkers to understand perceptions, practices, and barriers related to accessing healthcare for TB. Results Overall, 2,792 mineworkers and 94 HCWs completed the KAP survey, and 206 (171 current, 71 ex-) mineworkers participated in FGDs. Mineworkers and ex-mineworkers were knowledgeable about TB symptoms (cough; 94%), transmission (81.7%) and treatment (99.2%). Yet, barriers to seeking care were evident with 30% of mineworkers experiencing cough, and 19% reporting 2 or more TB symptoms at the time of the survey. The majority of mineworkers (70.9%) were aware of policies barring persons from working after a diagnosis of TB, and themes from FGDs and HCW comments (n = 32/62; 51.6%) recognized fear of job loss as a critical barrier to providing timely screening and appropriate care for TB among mineworkers. The majority (76.9%) of mineworkers indicated they would not disclose their TB status to their supervisor, but would be willing to share their diagnosis with their spouse (73.8%). Conclusion Fear of job loss, driven by governmental policy and mistrust in mining companies, is a major barrier to healthcare access for TB among mineworkers in Zambia. As a result of these findings, the government policy prohibiting persons from working in the mines following TB disease is being repealed. However, major reforms are urgently needed to mitigate TB among mineworkers, including ensuring the rights of mineworkers and their communities to healthy living and working environments, improved social responsibility of mining companies, and facilitating choice and access to affordable, timely, and high-quality healthcare services.

Background: The UNAIDS 90-90-90 Fast-Track targets provide a framework for assessing coverage of HIV testing services (HTS) and awareness of HIV status – the “first 90.” In Kenya, the bulk of HIV testing targets are aligned to the five highest HIV-burden counties. However, we do not know if most of the new HIV diagnoses are in these five highest-burden counties or elsewhere.Methods: We analyzed facility-level HTS data in Kenya from 1 October 2015 to 30 September 2016 to assess the spatial distribution of newly diagnosed HIV-positives. We used the Moran's Index (Moran's I) to assess global and local spatial auto-correlation of newly diagnosed HIV-positive tests and Kulldorff spatial scan statistics to detect hotspots of newly diagnosed HIV-positive tests. For aggregated data, we used Kruskal-Wallis equality-of-populations non-parametric rank test to compare absolute numbers across classes.Results: Out of 4,021 HTS sites, 3,969 (98.7%) had geocodes available. Most facilities (3,034, 76.4%), were not spatially autocorrelated for the number of newly diagnosed HIV-positives. For the rest, clustering occurred as follows; 438 (11.0%) were HH, 66 (1.7%) HL, 275 (6.9%) LH, and 156 (3.9%) LL. Of the HH sites, 301 (68.7%) were in high HIV-burden counties. Over half of 123 clusters with a significantly high number of newly diagnosed HIV-infected persons, 73(59.3%) were not in the five highest HIV-burden counties. Clusters with a high number of newly diagnosed persons had twice the number of positives per 1,000,000 tests than clusters with lower numbers (29,856 vs. 14,172).Conclusions: Although high HIV-burden counties contain clusters of sites with a high number of newly diagnosed HIV-infected persons, we detected many such clusters in low-burden counties as well. To expand HTS where most needed and reach the “first 90” targets, geospatial analyses and mapping make it easier to identify and describe localized epidemic patterns in a spatially dispersed epidemic like Kenya's, and consequently, reorient and prioritize HTS strategies.

Tuberculosis caused by concurrent infection with multiple Mycobacterium tuberculosis strains (i.e., mixed infection) challenges clinical and epidemiologic paradigms. We explored possible transmission mechanisms of mixed infection in a population-based, molecular epidemiology study in Botswana during 2012-2016. We defined mixed infection as multiple repeats of alleles at >2 loci within a discrete mycobacterial interspersed repetitive unit-variable-number tandem-repeat (MIRU-VNTR) result. We compared mixed infection MIRU-VNTR results with all study MIRU-VNTR results by considering all permutations at each multiple allele locus; matched MIRU-VNTR results were considered evidence of recently acquired strains and nonmatched to any other results were considered evidence of remotely acquired strains. Among 2,051 patients, 34 (1.7%) had mixed infection, of which 23 (68%) had recently and remotely acquired strains. This finding might support the mixed infection mechanism of recent transmission and simultaneous remote reactivation. Further exploration is needed to determine proportions of transmission mechanisms in settings where mixed infections are prevalent.

IntroductionHigh antiretroviral therapy (ART) coverage and high rates of viral load suppression (VLS) should reduce transmission of HIV, and ultimately, HIV incidence and the number of new HIV diagnoses out of the number tested (HIV positivity). We used 3 years of HIV program data in Kenya to assess whether trends in the number of new HIV diagnoses were associated with ART coverage and VLS rates and spatial-temporally auto-correlated at county level.MethodsWe analyzed routine program county-level aggregate data on ART coverage and VLS (proportion of persons on ART with VL

Background: In a spatially well known and dispersed HIV epidemic, identifying geographic clusters with significantly higher HIV prevalence is important for focusing interventions for people living with HIV (PLHIV). Methods: We used Kulldorff spatial-scan Poisson model to identify clusters with high numbers of HIV-infected persons 15–64 years old. We classified PLHIV as belonging to either higher prevalence or lower prevalence (HP/LP) clusters, then assessed distributions of sociodemographic and biobehavioral HIV risk factors and associations with clustering. Results: About half of survey locations, 112/238 (47%) had high rates of HIV (HP clusters), with 1.1–4.6 times greater PLHIV adults observed than expected. Richer persons compared with respondents in lowest wealth index had higher odds of belonging to a HP cluster, adjusted odds ratio (aOR) 1.61 [95% confidence interval (CI): 1.13 to 2.3], aOR 1.66 (95% CI: 1.09 to 2.53), aOR 3.2 (95% CI: 1.82 to 5.65), and aOR 2.28 (95% CI: 1.09 to 4.78) in second, middle, fourth, and highest quintiles, respectively. Respondents who perceived themselves to have greater HIV risk or were already HIV-infected had higher odds of belonging to a HP cluster, aOR 1.96 (95% CI: 1.13 to 3.4) and aOR 5.51 (95% CI: 2.42 to 12.55), respectively; compared with perceived low risk. Men who had ever been clients of female sex worker had higher odds of belonging to a HP cluster than those who had never been, aOR 1.47 (95% CI: 1.04 to 2.08); and uncircumcised men vs circumcised, aOR 3.2 (95% CI: 1.74 to 5.8). Conclusions: HIV infection in Kenya exhibits localized geographic clustering associated with sociodemographic and behavioral factors, suggesting disproportionate exposure to higher HIV risk. Identification of these clusters reveals the right places for targeting priority-tailored HIV interventions.

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.

Background: Since 2004, several African countries, including Namibia, have received assistance from the U.S. President's Emergency Plan for AIDS Relief (PEPFAR). Aims: Gains have been documented in the safety and number of collected units in these countries, but the distribution of blood has not been described. Methods: Nine years of data on blood requests and issues from Namibia were stratified by region to describe temporal and spatial changes in the number and type of blood components issued to Namibian healthcare facilities nationally. Results: Between 2004-2007 (early years of PEPFAR support) and 2008-2011 (peak years of PEPFAR support), the average number of red cell units issued annually increased by 23.5% in seven densely populated but less developed regions in northern Namibia; by 30% in two regions with urban centers; and by 35.1% in four sparsely-populated rural regions. Summary/Conclusions: Investments in blood safety and a policy decision to emphasize distribution of blood to underserved regions improved blood availability in remote rural areas and increased the proportion of units distributed as components. However, disparities persist in the distribution of blood between Namibia's urban and rural regions.

Background and Objectives Since 2004, several African countries, including Namibia, have received assistance from the U.S. President's Emergency Plan for AIDS Relief (PEPFAR). Gains have been documented in the safety and number of collected units in these countries, but the distribution of blood has not been described. Materials and Methods Nine years of data on blood requests and issues from Namibia were stratified by region to describe temporal and spatial changes in the number and type of blood components issued to Namibian healthcare facilities nationally. Results Between 2004 and 2007 (early years of PEPFAR support) and 2008–2011 (peak years of PEPFAR support), the average number of red cell units issued annually increased by 23.5% in seven densely populated but less-developed regions in northern Namibia; by 30% in two regions with urban centres; and by 35.1% in four sparsely populated rural regions. Conclusion Investments in blood safety and a policy decision to emphasize distribution of blood to underserved regions improved blood availability in remote rural areas and increased the proportion of units distributed as components. However, disparities persist in the distribution of blood between Namibia's urban and rural regions.

Introduction Using spatial–temporal analyses to understand coverage and trends in elimination of mother-to-child transmission of HIV (e-MTCT) efforts may be helpful in ensuring timely services are delivered to the right place. We present spatial–temporal analysis of seven years of HIV early infant diagnosis (EID) data collected from 12 districts in western Kenya from January 2007 to November 2013, during pre-Option B+ use. Methods We included in the analysis infants up to one year old. We performed trend analysis using extended Cochran–Mantel–Haenszel stratified test and logistic regression models to examine trends and associations of infant HIV status at first diagnosis with: early diagnosis ( Results Median age was two months, interquartile range 1.5–5.8 months. Unadjusted pooled positive rate was 11.8% in the seven-years period and declined from 19.7% in 2007 to 7.0% in 2013, p < 0.01. Uptake of testing ≤8 weeks after birth was under 50% in 2007 and increased to 64.1% by 2013, p < 0.01. By 2013, the overall standardized MTCT rate was 447 infections per 100,000 live births. Based on Bayesian deviance information criterion comparisons, the spatial–temporal model with maternal and infant covariates was best in explaining geographical variation in MTCT. Discussion Improved EID uptake and reduced MTCT rates are indicators of progress towards e-MTCT. Cojoined analysis of time and covariates in a spatial context provides a robust approach for explaining differences in programmatic impact over time. Conclusion During this pre-Option B+ period, the prevention of mother to child transmission program in this region has not achieved e-MTCT target of ≤50 infections per 100,000 live births. Geographical disparities in program achievements may signify gaps in spatial distribution of e-MTCT efforts and could indicate areas needing further resources and interventions.

Use of the Louisiana Immunization Network for Kids Statewide (LINKS) during the aftermath of Hurricane Katrina saved parents and immunization providers' time, money, and the inconvenience of having to unnecessarily revaccinate children displaced both inside and outside Louisiana. This immunization information system remained online via a backup system following the hurricane, thereby making immunization history data available to queries from healthcare providers caring for displaced persons both within Louisiana and throughout the United States. LINKS contained immunization records for approximately 1.5 million people of all ages at the time of the hurricane. Assessment of more than 21 000 successful electronic immunization queries of children and adolescents displaced outside Louisiana state boundaries from virtually all states estimates that more than $4.6 million was saved in revaccination expenses. The impact of recovered records for these children within Louisiana is certainly as critical. Our review illustrates the value of an immunization information system as a tool to support not only individuals, healthcare providers, and public health authorities but also the presidential vision to develop Electronic Health Records in the United States over the next 10 years.