BACKGROUND: Early identification of outbreaks remains a key component in continuing to reduce the burden of infectious disease in the United States. Previous studies have applied statistical methods to detect unexpected cases of disease in space or time. The objectives of our study were to assess the ability and timeliness of three spatio-temporal methods to detect known outbreaks of tuberculosis. METHODS: We used routinely available molecular and surveillance data to retrospectively assess the effectiveness of three statistical methods in detecting tuberculosis outbreaks: county-based log-likelihood ratio, cumulative sums, and a spatial scan statistic. RESULTS: Our methods identified 8 of the 9 outbreaks, and 6 outbreaks would have been identified 1-52 months (median=10 months) before local public health authorities identified them. Assuming no delays in data availability, 46 (59.7%) of the 77 patients in the 9 outbreaks were identified after our statistical methods would have detected the outbreak but before local public health authorities became aware of the problem. CONCLUSIONS: Statistical methods, when applied retrospectively to routinely collected tuberculosis data, can successfully detect known outbreaks, potentially months before local public health authorities become aware of the problem. The three methods showed similar results; no single method was clearly superior to the other two. Further study to elucidate the performance of these methods in detecting tuberculosis outbreaks will be done in a prospective analysis.

BACKGROUND: Quantifying subnational need for antiretroviral therapy (ART) for HIV is challenging because people living with HIV (PLHIV) access health facilities in areas that may differ from their residence. We defined and demonstrated new indicators for PLHIV treatment needed to guide health system target setting and resource allocation. SETTING: Botswana. METHODS: We extended Naomi, a Bayesian small-area model for estimating district-level HIV indicators from national household survey and HIV service delivery data. We used model outputs for ART seeking probabilities in neighboring districts to define the "PLHIV (attending)" indicator representing the estimated number of PLHIV who would seek treatment at health facilities in a district, and "Untreated PLHIV attending" representing gaps in ART service provision. Botswana 2021 district HIV estimates were used to demonstrate new outputs and assess the sensitivity to uncertainty in district population sizes. RESULTS: Across districts of Botswana, estimated adult ART coverage in December 2021 ranged 90%-96%. In the capital city Gaborone, there were 50,400 resident PLHIV and 64,200 receiving ART, of whom 24% (95% CI: 20 to 32) were estimated to reside in neighboring districts. Applying ART attendance probabilities gave a "PLHIV attending" denominator of 68,300 and unmet treatment need of 4100 adults (95% CI: 3000 to 5500) for Gaborone health facilities. The facility-based "PLHIV attending" denominator was less-sensitive to fluctuations in district population size assumptions. CONCLUSIONS: New indicators provided more consistent targets for HIV service provision, but are limited by ART data quality. This challenge will increase as treatment coverage reaches high levels and treatment gaps are smaller.

We investigated cross-sectional associations between children's neurodevelopment and their gut microbiota composition. Study children (36 months of age) lived in rural China (n = 46). Neurodevelopment was assessed using the Bayley Scales of Infant Development, 2nd Edition, yielding the Mental Developmental Index (MDI) and Psychomotor Developmental Index (PDI). Children's gut microbiota was assessed using 16S rRNA gene profiling. Microbial diversity was characterized using alpha diversity patterns. Additionally, 3 coabundance factors were determined for the 25 most abundant taxa. Multivariable linear regression models were constructed to examine the relationships between Bayley scores (MDI and PDI) and children's gut microbiota. In adjusted models, MDI and PDI scores were not associated with alpha diversity indices. However, in adjusted models, MDI and PDI scores were positively associated with the first coabundance factor, which captured positive loadings for the genera Faecalibacterium, Sutterella, and Clostridium cluster XIVa. For an interquartile range increase in the first coabundance factor, MDI scores increased by 3.9 points [95% confidence interval (CI): 0, 7.7], while PDI scores increased by 8.6 points (95% CI 3.1, 14). Our results highlight the potential for gut microbial compositional characteristics to be important correlates of children's Bayley Scales performance at 36 months of age.

Residents of long-term care facilities (LTCFs), particularly those in skilled nursing facilities (SNFs), have experienced disproportionately high levels of COVID-19-associated morbidity and mortality and were prioritized for early COVID-19 vaccination (1,2). However, this group was not included in COVID-19 vaccine clinical trials, and limited postauthorization vaccine effectiveness (VE) data are available for this critical population (3). It is not known how well COVID-19 vaccines protect SNF residents, who typically are more medically frail, are older, and have more underlying medical conditions than the general population (1). In addition, immunogenicity of the Pfizer-BioNTech vaccine was found to be lower in adults aged 65-85 years than in younger adults (4). Through the CDC Pharmacy Partnership for Long-Term Care Program, SNF residents and staff members in Connecticut began receiving the Pfizer-BioNTech COVID-19 vaccine on December 18, 2020 (5). Administration of the vaccine was conducted during several on-site pharmacy clinics. In late January 2021, the Connecticut Department of Public Health (CT DPH) identified two SNFs experiencing COVID-19 outbreaks among residents and staff members that occurred after each facility's first vaccination clinic. CT DPH, in partnership with CDC, performed electronic chart review in these facilities to obtain information on resident vaccination status and infection with SARS-CoV-2, the virus that causes COVID-19. Partial vaccination, defined as the period from >14 days after the first dose through 7 days after the second dose, had an estimated effectiveness of 63% (95% confidence interval [CI] = 33%-79%) against SARS-CoV-2 infection (regardless of symptoms) among residents within these SNFs. This is similar to estimated effectiveness for a single dose of the Pfizer-BioNTech COVID-19 vaccine in adults across a range of age groups in noncongregate settings (6) and suggests that to optimize vaccine impact among this population, high coverage with the complete 2-dose series should be recommended for SNF residents and staff members.

INTRODUCTION: Etiology studies of severe acute respiratory infections (SARI) in adults are limited. We studied potential etiologies of SARI among adults in six countries using multi-pathogen diagnostics. METHODS: We enrolled both adults with SARI (acute respiratory illness onset with fever and cough requiring hospitalization) and asymptomatic adults (adults hospitalized with non-infectious illnesses, non-household members accompanying SARI patients, adults enrolled from outpatient departments, and community members) in each country. Demographics, clinical data, and nasopharyngeal and oropharyngeal specimens were collected from both SARI patients and asymptomatic adults. Specimens were tested for presence of 29 pathogens utilizing the Taqman® Array Card platform. We applied a non-parametric Bayesian regression extension of a partially latent class model approach to estimate proportions of SARI caused by specific pathogens. RESULTS: We enrolled 2,388 SARI patients and 1,135 asymptomatic adults from October 2013 through October 2015. We detected ≥1 pathogen in 76% of SARI patients and 67% of asymptomatic adults. Haemophilus influenzae and Streptococcus pneumoniae were most commonly detected (≥23% of SARI patients and asymptomatic adults). Through modeling, etiology was attributed to a pathogen in most SARI patients (range among countries: 57.3-93.2%); pathogens commonly attributed to SARI etiology included influenza A (14.4-54.4%), influenza B (1.9-19.1%), rhino/enterovirus (1.8-42.6%), and RSV (3.6-14.6%). CONCLUSIONS: Use of multi-pathogen diagnostics and modeling enabled attribution of etiology in most adult SARI patients, despite frequent detection of multiple pathogens in the upper respiratory tract. Seasonal flu vaccination and development of RSV vaccine would likely reduce the burden of SARI in these populations.

BACKGROUND: Globally, over 400,000 neonatal deaths in 2015 were attributed to sepsis, however, the incidence and etiologies of these infections are largely unknown in low-middle income countries. We aimed to determine incidence and etiology of community-acquired early-onset (<72 hours age) sepsis (EOS) using culture and molecular diagnostics. METHODS: This was a prospective observational study, in which we conducted a surveillance for pathogens using a combination of blood culture and a polymerase chain reaction (PCR)-based test. Blood culture was performed on all neonates with suspected EOS. Among the subset fulfilling criteria for protocol-defined EOS, blood and nasopharyngeal (NP) respiratory swabs were tested by quantitative real-time reverse-transcriptase PCR using a Taqman Array Card (TAC) with 15 bacterial and 12 viral targets. Blood and NP samples from 312 healthy newborns were also tested by TAC to estimate background positivity rates. We used variant latent-class methods to attribute etiologies and calculate pathogen-specific proportions and incidence rates. RESULTS: We enrolled 2,624 neonates with suspected EOS and from these 1,231 newborns met criteria for protocol-defined EOS (incidence- 39.3/1,000 live-births). Using the partially latent-class modelling, only 26.7% cases with protocol-defined EOS had attributable etiology, and the largest pathogen proportion were Ureaplasma spp. (5.4%; 95%CI: 3.6-8.0) and group B Streptococcus (GBS) (4.8%; 95%CI: 4.1-5.8), and no etiology was attributable for 73.3% of cases. Blood cultures were positive in 99/1,231 (8.0%) with protocol-defined EOS (incidence- 3.2/1,000 live-births). Leading pathogens on blood culture included GBS (35%) and viridans streptococci (24%). Ureaplasma spp. was the most common organism identified on TAC among cases with protocol-defined EOS. CONCLUSION: Using a combination of blood culture and a PCR-based test the common pathogens isolated in neonates with sepsis were Ureaplasma spp. and GBS. Despite documenting higher rates of protocol-defined EOS and using a combination of tests, the etiology for EOS remains elusive.

SETTING: National Tuberculosis (TB) Program sites in northwest Cambodia. OBJECTIVE: To evaluate the impact of Xpert((R)) MTB/RIF at point of care (POC) as compared to non-POC sites on the diagnostic evaluation of people living with the human immunodeficiency virus (PLHIV) with TB symptoms and patients with possible multidrug-resistant (MDR) TB. DESIGN: Observational cohort of patients undergoing routine diagnostic evaluation for TB following the rollout of Xpert. RESULTS: Between October 2011 and June 2013, 431 of 822 (52%) PLHIV with TB symptoms and 240/493 (49%) patients with possible MDR-TB underwent Xpert. Xpert was more likely to be performed when available as POC. A smaller proportion of PLHIV at POC sites were diagnosed with TB than at non-POC sites; however, at POC sites, a higher proportion of those diagnosed with TB were bacteriologically positive. There was poor agreement between Xpert and other tests such as smear microscopy and culture. Overall, the evaluation of patients with possible MDR-TB increased following Xpert rollout, yet for patients confirmed as having drug resistance on drug susceptibility testing, only 46% had rifampin resistance that would be identified with Xpert. CONCLUSION: Although utilization of Xpert was low, it may have contributed to an increase in evaluations for possible MDR-TB and a decline in empiric treatment for PLHIV when available as POC.

OBJECTIVE: To describe the implementation and utilization of the Xpert MTB/RIF (Xpert) assay to diagnose tuberculosis (TB) among people living with the human immunodeficiency virus/acquired immune-deficiency syndrome (HIV/AIDS, PLHA) in Cambodia. DESIGN: Following the rollout of Xpert, an evaluation was conducted in four provinces of Cambodia from March to December 2012 to determine the utilization, performance, and turnaround time (TAT) of Xpert among PLHA. Data were collected from paper-based patient registers. RESULTS: Of 497 PLHA with a positive TB symptom screen, 357 (72%) were tested with smear microscopy, and 250 (50%) with Xpert; 25 (10%) PLHA tested with Xpert were positive for TB and none were rifampicin-resistant. The utilization of Xpert increased from 23% to 75%, with a median TAT of 1 day. Across districts, utilization ranged from zero to 85%, while the TAT ranged from zero to 22 days. CONCLUSION: While early data show increasing utilization of Xpert for PLHA with a positive symptom screen, most patients underwent smear microscopy as an initial diagnostic test. Training delays and challenges associated with specimen referral may have contributed to variability in Xpert uptake and TAT, particularly for sites without onsite Xpert testing. Enhanced programmatic support, particularly for specimen referral and results reporting, may facilitate appropriate utilization.

We combined routinely reported tuberculosis (TB) patient characteristics with genotyping data and measures of geospatial concentration to predict which small clusters (i.e., consisting of only 3 TB patients) in the United States were most likely to become outbreaks of at least 6 TB cases. Of 146 clusters analyzed, 16 (11.0%) grew into outbreaks. Clusters most likely to become outbreaks were those in which at least 1 of the first 3 patients reported homelessness or excess alcohol or illicit drug use or was incarcerated at the time of TB diagnosis and in which the cluster grew rapidly (i.e., the third case was diagnosed within 5.3 months of the first case). Of 17 clusters with these characteristics and therefore considered high risk, 9 (53%) became outbreaks. This retrospective cohort analysis of clusters in the United States suggests that routinely reported data may identify small clusters that are likely to become outbreaks and which are therefore candidates for intensified contact investigations.

BACKGROUND: Tuberculosis is the leading cause of death among people living with HIV and frequently transmitted among this susceptible group. Transmission can be reduced by infection control practices. Simple, evidence-based methods to identify patients who should be isolated are not well described in the literature. We sought to identify a simple, sensitive symptom or symptom combination that healthcare providers in resource-limited settings can use to identify and isolate persons living with HIV with highly infectious TB. METHODS: Participants from eight outpatient facilities in Cambodia, Thailand, and Vietnam underwent an extensive evaluation for tuberculosis. Patients with ≥ 1 positive sputum smear and Mycobacterium tuberculosis culture growth from a pulmonary site were defined as having highly infectious tuberculosis. We calculated sensitivity and prevalence of individual symptoms and >1,000 symptom combinations. RESULTS: Of 1,980 participants, 272 (14%) had tuberculosis. Forty percent (n=109) were highly infectious. Sensitivity for detecting highly infectious tuberculosis was highest for having the following symptoms in the past month: weight loss (84%), cough (83%), fever (81%) and fatigue (78%); however, these symptoms were found in 46%-54% of all participants. Having two or three of four symptoms (prevalence, 26%-47%)-weight loss, fever, current cough, and night sweats-was 72-90% sensitive for highly infectious tuberculosis. CONCLUSIONS: The two or three of four symptom combinations of weight loss, fever, current cough, and night sweats, which are the same symptoms comprising the current World Health Organization-recommended tuberculosis diagnostic screen, are sensitive for detecting highly infectious tuberculosis in people living with HIV.