Demographic and Geographic Characterization of Excess Mortality During the COVID-19 Pandemic in Baltimore City, Maryland, March 2020 to March 2021.

Estimates of excess mortality can provide insight into direct and indirect impacts of the coronavirus disease 2019 (COVID-19) pandemic beyond deaths specifically attributed to COVID-19. We analyzed death certificate data from Baltimore City, Maryland, from March 1, 2020, to March 31, 2021, and found that 1,725 individuals (95% confidence interval: 1,495, 1,954) died in excess of what was expected from all-cause mortality trends in 2016-2019; 1,050 (61%) excess deaths were attributed to COVID-19. Observed mortality was 23%-32% higher than expected among individuals aged 50 years and older. Non-White residents of Baltimore City also experienced 2 to 3 times higher rates of excess mortality than White residents (e.g., 37.4 vs. 10.7 excess deaths per 10,000 population among Black residents vs. White residents). There was little to no observed excess mortality among residents of hospice, long-term care, and nursing home facilities, despite accounting for nearly 30% (312/1,050) of recorded COVID-19 deaths. There was significant geographic variation in excess mortality within the city, largely following racial population distributions. These results demonstrate the substantial and unequal impact of the COVID-19 pandemic on Baltimore City residents and the importance of building robust, timely surveillance systems to track disparities and inform targeted strategies to remediate the impact of future epidemics.

Decline in prevalence of tuberculosis following an intensive case finding campaign and the COVID-19 pandemic in an urban Ugandan community.

BACKGROUND: Systematic screening is a potential tool for reducing the prevalence of tuberculosis (TB) and counteracting COVID-19-related disruptions in care. Repeated community-wide screening can also measure changes in the prevalence of TB over time. METHODS: We conducted serial, cross-sectional TB case finding campaigns in one community in Kampala, Uganda, in 2019 and 2021. Both campaigns sought sputum for TB testing (Xpert MTB/RIF Ultra) from all adolescents and adults. We estimated the prevalence of TB among screening participants in each campaign and compared characteristics of people with TB across campaigns. We simultaneously enrolled and characterised community residents who were diagnosed with TB through routine care and assessed trends in facility-based diagnosis. RESULTS: We successfully screened 12 033 community residents (35% of the estimated adult/adolescent population) in 2019 and 11 595 (33%) in 2021. In 2019, 0.94% (95% CI: 0.77% to 1.13%) of participants tested Xpert positive (including trace). This proportion fell to 0.52% (95% CI: 0.40% to 0.67%) in 2021; the prevalence ratio was 0.55 (95% CI: 0.40 to 0.75)). There was no change in the age (median 26 vs 26), sex (56% vs 59% female) or prevalence of chronic cough (49% vs 54%) among those testing positive. By contrast, the rate of routine facility-based diagnosis remained steady in the 8 months before each campaign (210 (95% CI: 155 to 279) vs 240 (95% CI: 181 to 312) per 100 000 per year). CONCLUSIONS: Following an intensive initial case finding campaign in an urban Ugandan community in 2019, the burden of prevalent TB as measured by systematic screening had decreased by 45% in 2021, despite the intervening COVID-19 pandemic.

Methods for measuring short-term geographical mobility used in infectious disease research: a scoping review protocol.

INTRODUCTION: Geographical mobility, the movement of individuals or populations, may increase an individual's risk of acquiring or transmitting infectious diseases, including HIV, tuberculosis, malaria and COVID-19. Many studies have collected information on short-term mobility through self-reported travel histories or using GPS trackers, but there has been no consistent conceptualisation and operationalisation of such geographical mobility in global health research. This protocol aims to describe and synthesise different approaches to measuring short-term mobility. METHODS AND ANALYSIS: We will search three databases (PubMed, Embase and Global Health) for peer-reviewed articles. After removing duplicates, two reviewers will first screen the titles and abstracts and then proceed to full-text screening. We will include studies that measure mobility at the individual level in the context of infectious diseases, including clinical trials, epidemiological studies and analyses of register data. Additional articles for inclusion may be identified through review of references in selected papers. We will summarise the method of data collection (GPS trackers, cellphones, retrospective self-report, travel journal, etc) and the specific measures used (overnight travel, having a secondary residence, travel outside of district, etc). ETHICS AND DISSEMINATION: This study consists of reviewing and abstracting existing data from publicly available materials, and therefore does not require ethical approval. The results of this study will be submitted for peer reviewed publication and may be presented at a relevant global health conference.

Number Needed to Screen for Tuberculosis Disease Among Children: A Systematic Review.

CONTEXT: Improving detection of pediatric tuberculosis (TB) is critical to reducing morbidity and mortality among children. OBJECTIVE: We conducted a systematic review to estimate the number of children needed to screen (NNS) to detect a single case of active TB using different active case finding (ACF) screening approaches and across different settings. DATA SOURCES: We searched 4 databases (PubMed, Embase, Scopus, and the Cochrane Library) for articles published from November 2010 to February 2020. STUDY SELECTION: We included studies of TB ACF in children using symptom-based screening, clinical indicators, chest x-ray, and Xpert. DATA EXTRACTION: We indirectly estimated the weighted mean NNS for a given modality, location, and population using the inverse of the weighted prevalence. We assessed risk of bias using a modified AXIS tool. RESULTS: We screened 27 221 titles and abstracts, of which we included 31 studies of ACF in children < 15 years old. Symptom-based screening was the most common screening modality (weighted mean NNS: 257 [range, 5-undefined], 19 studies). The weighted mean NNS was lower in both inpatient (216 [18-241]) and outpatient (67 [5-undefined]) settings (107 [5-undefined]) compared with community (1117 [28-5146]) and school settings (464 [118-665]). Risk of bias was low. LIMITATIONS: Heterogeneity in the screening modalities and populations make it difficult to draw conclusions. CONCLUSIONS: We identified a potential opportunity to increase TB detection by screening children presenting in health care settings. Pediatric TB case finding interventions should incorporate evidence-based interventions and local contextual information in an effort to detect as many children with TB as possible.

Characterization of geographic mobility among participants in facility- and community-based tuberculosis case finding in urban Uganda.

BACKGROUND: International and internal migration are recognized risk factors for tuberculosis (TB). Geographic mobility, including travel for work, education, or personal reasons, may also play a role in TB transmission, but this relationship is poorly defined. We aimed to define geographic mobility among participants in facility- and community-based TB case finding in Kampala, Uganda, and to assess associations between mobility, access to care, and TB disease. METHODS: We included consecutive individuals age ≥15 years diagnosed with TB disease through either routine health facility practices or community-based case finding (consisting of door-to-door testing, venue-based screening, and contact investigation). Each case was matched with one (for community-based enrollment) or two (health facility enrollment) TB-negative controls. We conducted a latent class analysis (LCA) of eight self-reported characteristics to identify and define mobility; we selected the best-fit model using Bayesian Information Criterion. We assessed associations between mobility and TB case status using multivariable conditional logistic regression. RESULTS: We enrolled 267 cases and 432 controls. Cases were more likely than controls to have been born in Kampala (p<0.001); there was no difference between cases and controls for remaining mobility characteristics. We selected a two-class LCA model; the "mobile" class was perfectly correlated with a single variable: travel (>3 km) from residence ≥2 times per month. Mobility was associated with a 28% reduction in odds of being a TB case (adjusted matched odds ratio 0.72 [95% confidence interval 0.49, 1.06]). CONCLUSION: Frequency of out-of-neighborhood travel is an easily measured variable that correlates closely with predicted mobility class membership. Mobility was associated with decreased risk of TB disease; this may be in part due to the higher socioeconomic status of mobile individuals in this population. However, more research is needed to improve assessment of mobility and understand how mobility affects disease risk and transmission.

The Spectrum of Tuberculosis Disease in an Urban Ugandan Community and Its Health Facilities.

BACKGROUND: New, sensitive diagnostic tests facilitate identification and investigation of milder forms of tuberculosis (TB) disease. We used community-based TB testing with the Xpert MTB/RIF Ultra assay ("Ultra") to characterize individuals with previously undiagnosed TB and compare them to those from the same community who were diagnosed with TB through routine care. METHODS: We offered community-based sputum Ultra testing to adult residents of a well-defined area (population 34 000 adults) in Kampala, Uganda, via door-to-door screening and venue-based testing, then used detailed interview and laboratory testing to characterize TB-positive individuals. We compared these individuals to residents diagnosed with pulmonary TB at local health facilities and a representative sample of residents without TB (controls). RESULTS: Of 12 032 residents with interpretable Ultra results, 113 (940 [95% confidence interval {CI}, 780-1130] per 100 000) tested positive, including 71 (63%) positive at the lowest (trace) level. A spectrum of TB disease was observed in terms of chronic cough (93% among health facility-diagnosed cases, 77% among residents with positive community-based Ultra results at levels above trace, 33% among trace-positive community participants, and 18% among TB-negative controls), TB symptom prevalence (99%, 87%, 60%, and 38%, respectively), and C-reactive protein (75th percentile: 101 mg/L, 28 mg/L, 6 mg/L, and 4 mg/L, respectively). Community-diagnosed cases were less likely than health facility-diagnosed cases to have human immunodeficiency virus coinfection or previous TB. The specificity of Ultra was 99.4% (95% CI, 99.2%-99.5%) relative to a single spot sputum culture. CONCLUSIONS: People with undiagnosed prevalent TB in the community have different characteristics than those diagnosed with pulmonary TB in health facilities. Newer diagnostic tests may identify a group of people with early or very mild disease.

Spatial distribution of people diagnosed with tuberculosis through routine and active case finding: a community-based study in Kampala, Uganda.

BACKGROUND: Routine tuberculosis (TB) notifications are geographically heterogeneous, but their utility in predicting the location of undiagnosed TB cases is unclear. We aimed to identify small-scale geographic areas with high TB notification rates based on routinely collected data and to evaluate whether these areas have a correspondingly high rate of undiagnosed prevalent TB. METHODS: We used routinely collected data to identify geographic areas with high TB notification rates and evaluated the extent to which these areas correlated with the location of undiagnosed cases during a subsequent community-wide active case finding intervention in Kampala, Uganda. We first enrolled all adults who lived within 35 contiguous zones and were diagnosed through routine care at four local TB Diagnosis and Treatment Units. We calculated average monthly TB notification rates in each zone and defined geographic areas of "high risk" as zones that constituted the 20% of the population with highest notification rates. We compared the observed proportion of TB notifications among residents of these high-risk zones to the expected proportion, using simulated estimates based on population size and random variation alone. We then evaluated the extent to which these high-risk zones identified areas with high burdens of undiagnosed TB during a subsequent community-based active case finding campaign using a chi-square test. RESULTS: We enrolled 45 adults diagnosed with TB through routine practices and who lived within the study area (estimated population of 49 527). Eighteen zones reported no TB cases in the 9-month period; among the remaining zones, monthly TB notification rates ranged from 3.9 to 39.4 per 100 000 population. The five zones with the highest notification rates constituted 62% (95% CI: 47-75%) of TB cases and 22% of the population-significantly higher than would be expected if population size and random chance were the only determinants of zone-to-zone variation (48%, 95% simulation interval: 40-59%). These five high-risk zones accounted for 42% (95% CI: 34-51%) of the 128 cases detected during the subsequent community-based case finding intervention, which was significantly higher than the 22% expected by chance (P < 0.001) but lower than the 62% of cases notified from those zones during the pre-intervention period (P = 0.02). CONCLUSIONS: There is substantial heterogeneity in routine TB notification rates at the zone level. Using facility-based TB notification rates to prioritize high-yield areas for active case finding could double the yield of such case-finding interventions.

Is distance associated with tuberculosis treatment outcomes? A retrospective cohort study in Kampala, Uganda.

BACKGROUND: Challenges accessing nearby health facilities may be a barrier to initiating and completing tuberculosis (TB) treatment. We aimed to evaluate whether distance from residence to health facility chosen for treatment is associated with TB treatment outcomes. METHODS: We conducted a retrospective cohort study of all patients initiating TB treatment at six health facilities in Kampala from 2014 to 2016. We investigated associations between distance to treating facility and unfavorable TB treatment outcomes (death, loss to follow up, or treatment failure) using multivariable Poisson regression. RESULTS: Unfavorable treatment outcomes occurred in 20% (339/1691) of TB patients. The adjusted relative risk (aRR) for unfavorable treatment outcomes (compared to treatment success) was 0.87 (95% confidence interval [CI] 0.70, 1.07) for patients living ≥2 km from the facility compared to those living closer. When we separately compared each type of unfavorable treatment outcome to favorable outcomes, those living ≥2 km from the facility had increased risk of death (aRR 1.42 [95%CI 0.99, 2.03]) but decreased risk for loss to follow-up (aRR 0.57 [95%CI 0.41, 0.78]) than those living within 2 km. CONCLUSIONS: Distance from home residence to TB treatment facility is associated with increased risk of death but decreased risk of loss to follow up. Those who seek care further from home may have advanced disease, but once enrolled may be more likely to remain in treatment.