Tradition und Transformation: polyphone Wissensfigurationen in der Historia von D. Johann Fausten

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Seroprevalence of SARS-CoV-2 antibody among individuals aged above 15 years and residing in congregate settings in Dire Dawa city administration, Ethiopia

Background Determining the extent of seropositivity of SARS-CoV-2 antibody has the potential to guide prevention and control efforts. We aimed to determine the seroprevalence of SARS-CoV-2 antibody among individuals aged above15 years and residing in the congregate settings of Dire Dawa city administration, Ethiopia. Method We analyzed COVID-19 seroprevalence data on 684 individuals from a community based cross-sectional survey conducted among individuals aged above 15 years and residing in congregate settings in Dire Dawa from June 15 to July 30, 2020. Data were collected using interview and blood sample collection. Participants were asked about demographic characteristics, COVID-19 symptoms, and their practice of preventive measures. Seroprevalence was determined using SARS-CoV-2 IgG test. Bivariate and multivariate multilevel mixed effects logistic regression model was fitted and statistical significance was set at p value < 0.05. Result The estimated SARS-CoV-2 seroprevalence was 3.2% (95 % CI 2.0–4.8) in the study region with no differences by age and sex but considerable differences were observed by self-reported practice of COVID-19 preventive measures. The cluster effect is not significant (P = 0.396) which has suggested no evidence of heterogeneity in SARS-CoV-2 seroprevalence among the clusters. The odds of SARS-CoV-2 antibody seroprevalence were higher for individuals who were employed and work by moving from home to work area (AOR; 9.73 95% CI 2.51, 37.68), reported of not wearing facemasks when leaving home (AOR; 6.4 95% CI 2.30, 17.66) and did not practice physical distancing measures (AOR; 10 95% CI 3.01, 33.20) compared to their counterparts, respectively. Our estimated seroprevalence of SARS-CoV-2 among participants who reported not to have practiced social distancing measures was 12.8 (95% CI, 7.0, 19) and 1.5 (95% CI, 0.5, 2.5) among those who reported of practicing them. More than 80% of study participants reported of implementing infection prevention measures (face masks and physical distancing recommendations). Conclusion The detected SARS-CoV-2 seroprevalence among the study participants was low at the time of the survey indicating higher proportion of population yet to be infected. COVID-19 preventive measures were associated with reduced seroprevalence and should be promoted to avoid transmission to the uninfected majority

Assortative social mixing and sex disparities in tuberculosis burden

Globally, men have higher tuberculosis (TB) burden but the mechanisms underlying this sex disparity are not fully understood. Recent surveys of social mixing patterns have established moderate preferential within-sex mixing in many settings. This assortative mixing could amplify differences from other causes. We explored the impact of assortative mixing and factors differentially affecting disease progression and detection using a sex-stratified deterministic TB transmission model. We explored the influence of assortativity at disease-free and endemic equilibria, finding stronger effects during invasion and on increasing male:female prevalence (M:F) ratios than overall prevalence. Variance-based sensitivity analysis of endemic equilibria identified differential progression as the most important driver of M:F ratio uncertainty. We fitted our model to prevalence and notification data in exemplar settings within a fully Bayesian framework. For our high M:F setting, random mixing reduced equilibrium M:F ratios by 12% (95% CrI 0–30%). Equalizing male case detection there led to a 20% (95% CrI 11–31%) reduction in M:F ratio over 10 years—insufficient to eliminate sex disparities. However, this potentially achievable improvement was associated with a meaningful 8% (95% CrI 4–14%) reduction in total TB prevalence over this time frame

Geospatial clustering and modelling provide policy guidance to distribute funding for active TB case finding in Ethiopia

Tuberculosis (TB) exhibits considerable spatial heterogeneity, occurring in clusters that may act as hubs of community transmission. We evaluated the impact of an intervention targeting spatial TB hotspots in a rural region of Ethiopia. To evaluate the impact of targeted active case finding (ACF), we used a spatially structured mathematical model that has previously been described. From model equilibrium, we simulated the impact of a hotspot-targeted strategy (HTS) on TB incidence ten years from intervention commencement and the associated cost-effectiveness. HTS was also compared with an untargeted strategy (UTS). We used logistic cost-coverage analysis to estimate cost-effectiveness of interventions. At a community screening coverage level of 95% in a hotspot region, which corresponds to screening 20% of the total population, HTS would reduce overall TB incidence by 52% compared with baseline. For UTS to achieve an equivalent effect, it would be necessary to screen more than 80% of the total population. Compared to the existing passive case detection strategy, the HTS at a CDR of 75 percent in hotspot regions is expected to avert 1,023 new TB cases over ten years saving USD 170 per averted case. Similarly, at the same CDR, the UTS will detect 1316 cases over the same period saving USD 3 per averted TB case. The incremental-cost effectiveness-ratio (ICER) of UTS compared with HTS is USD 582 per averted case corresponding to 293 more TB cases averted at an additional cost of USD 170,700. Where regional TB program spending was capped at current levels, maximum gains in incidence reduction were seen when the regional budget was shared between hotspots and non-hotspot regions in the ratio of 40% to 60%. Our analysis suggests that a spatially targeted strategy is efficient and cost-saving, with the potential for significant reduction in overall TB burden

Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics

Tuberculosis (TB) killed more people globally than any other single pathogen over the past decade. Where surveillance is weak, estimating TB burden estimates uses modeling. In many African countries, increases in HIV prevalence and antiretroviral therapy have driven dynamic TB epidemics, complicating estimation of burden, trends, and potential intervention impact. We therefore develop a novel age-structured TB transmission model incorporating evolving demographic, HIV and antiretroviral therapy effects, and calibrate to TB prevalence and notification data from 12 African countries. We use Bayesian methods to include uncertainty for all TB model parameters, and estimate age-specific annual risks of TB infection, finding up to 16.0%/year in adults, and the proportion of TB incidence from recent (re)infection, finding a mean across countries of 34%. Rapid reduction of the unacceptably high burden of TB in high HIV prevalence settings will require interventions addressing progression as well as transmission

TB Hackathon: Development and Comparison of Five Models to Predict Subnational Tuberculosis Prevalence in Pakistan

Pakistan’s national tuberculosis control programme (NTP) is among the many programmes worldwide that value the importance of subnational tuberculosis (TB) burden estimates to support disease control efforts, but do not have reliable estimates. A hackathon was thus organised to solicit the development and comparison of several models for small area estimation of TB. The TB hackathon was launched in April 2019. Participating teams were requested to produce district-level estimates of bacteriologically positive TB prevalence among adults (over 15 years of age) for 2018. The NTP provided case-based data from their 2010–2011 TB prevalence survey, along with data relating to TB screening, testing and treatment for the period between 2010–2011 and 2018. Five teams submitted district-level TB prevalence estimates, methodological details and programming code. Although the geographical distribution of TB prevalence varied considerably across models, we identified several districts with consistently low notification-to-prevalence ratios. The hackathon highlighted the challenges of generating granular spatiotemporal TB prevalence forecasts based on a cross-sectional prevalence survey data and other data sources. Nevertheless, it provided a range of approaches to subnational disease modelling. The NTP’s use and plans for these outputs shows that, limitations notwithstanding, they can be valuable for programme planning

TB hackathon : development and comparison of five models to predict subnational tuberculosis prevalence in Pakistan

Pakistan's national tuberculosis control programme (NTP) is among the many programmes worldwide that value the importance of subnational tuberculosis (TB) burden estimates to support disease control efforts, but do not have reliable estimates. A hackathon was thus organised to solicit the development and comparison of several models for small area estimation of TB. The TB hackathon was launched in April 2019. Participating teams were requested to produce district-level estimates of bacteriologically positive TB prevalence among adults (over 15 years of age) for 2018. The NTP provided case-based data from their 2010-2011 TB prevalence survey, along with data relating to TB screening, testing and treatment for the period between 2010-2011 and 2018. Five teams submitted district-level TB prevalence estimates, methodological details and programming code. Although the geographical distribution of TB prevalence varied considerably across models, we identified several districts with consistently low notification-to-prevalence ratios. The hackathon highlighted the challenges of generating granular spatiotemporal TB prevalence forecasts based on a cross-sectional prevalence survey data and other data sources. Nevertheless, it provided a range of approaches to subnational disease modelling. The NTP's use and plans for these outputs shows that, limitations notwithstanding, they can be valuable for programme planning

When are patients lost to follow-up in pre-antiretroviral therapy care? a retrospective assessment of patients in an Ethiopian rural hospital

BACKGROUND: There is concern about the increasing rates of loss to follow-up (LTFU) among pre-antiretroviral therapy (pre-ART) patients in Ethiopia. Little information is available regarding the time when pre-ART patients are lost to follow-up in the country. This study assessed the time when LTFU occurs as well as the associated factors among adults enrolled in pre-ART care in an Ethiopian rural hospital. METHODS: Data of all adult pre-ART patients enrolled at the Sheka Zonal Hospital between 2010 and 2013 were reviewed. Patients were considered lost to follow-up if they failed to keep scheduled appointments for more than 90 days. The Cox proportional hazards regression model was used to assess factors associated with time until LTFU. The Kaplan-Meier survival table was used to compare the LTFU experiences of patients, segregated by significant predictors. RESULTS: A total of 626 pre-ART patients were followed for 319.92 person-years of observation (PYOs) from enrolment to pre-ART outcomes, with an overall LTFU rate of 55.8 per 100 PYOs. A total of 178 (28.4%) pre-ART patients were lost to follow-up, 93% of which occurred within the first six months. The median follow-up time was 6.13 months. The independent predictors included: not having been started on co-trimoxazole prophylaxis (adjusted hazard ratio [AHR] = 1.77, 95% confidence interval [CI], 1.12-2.79), a baseline CD4 count of or above 350 cells/mm3 (AHR = 1.87, 95%CI, 1.02-3.45), and an undisclosed HIV status (AHR = 3.04, 95%CI, 2.07-4.45). CONCLUSION: A significant proportion of pre-ART patients is lost to follow-up. Not having been started on co-trimoxazole prophylaxis, presenting to care with a baseline CD4 cell count ≥350 cells/mm(3), and an undisclosed HIV status were significant predictors of LTFU among pre-ART patients. Thus, close monitoring and tracking of patients during this period is highly recommended. Those patients with identified risk factors deserve special attention