Background: To stop tuberculosis (TB), the leading infectious cause of death globally, we need to better understand transmission risk factors. Although many studies have identified associations between individual-level covariates and pathogen genetic relatedness, few have identified characteristics of transmission pairs or explored how closely covariates associated with genetic relatedness mirror those associated with transmission. Methods: We simulated a TB-like outbreak with pathogen genetic data and estimated odds ratios (ORs) to correlate each covariate and genetic relatedness. We used a naive Bayes approach to modify the genetic links and nonlinks to resemble the true links and nonlinks more closely and estimated modified ORs with this approach. We compared these two sets of ORs with the true ORs for transmission. Finally, we applied this method to TB data in Hamburg, Germany, and Massachusetts, USA, to find pair-level covariates associated with transmission. Results: Using simulations, we found that associations between covariates and genetic relatedness had the same relative magnitudes and directions as the true associations with transmission, but biased absolute magnitudes. Modifying the genetic links and nonlinks reduced the bias and increased the confidence interval widths, more accurately capturing error. In Hamburg and Massachusetts, pairs were more likely to be probable transmission links if they lived in closer proximity, had a shorter time between observations, or had shared ethnicity, social risk factors, drug resistance, or genotypes. Conclusions: We developed a method to improve the use of genetic relatedness as a proxy for transmission, and aid in understanding TB transmission dynamics in low-burden settings.
The purpose of this study was to determine the effect of an automated procedure logging (APL) system on the number of procedures logged by emergency medicine (EM) residents. Secondary objectives were to assess the APL's effect on completeness and accuracy of procedure logging and to measure resident compliance with the system.This was a before-and-after study conducted at a university-affiliated, urban medical center, with an annual emergency department census of >130,000. The EM residency is a 4-year, Residency Review Committee (RRC)-accredited program with 12 residents per year. We developed software to electronically search and abstract resident procedures documented in the electronic medical record (EMR) and automatically export them into a Web-based residency management system. We compared the mean daily number of procedures logged for two 6-month periods: October 1, 2009, to March 31, 2010 (pre-APL), and October 1, 2010, to March 31, 2011 (post-APL), using a two-sample t-test. We also generated a random sample of 231 logged procedures from both the pre- and post-APL time periods to assess for completeness and accuracy of data transfer. Completeness and accuracy in the pre- and post-APL periods were compared using Fisher's exact test. Aggregate resident compliance with the system was also measured.The mean daily number of procedures logged increased by 168% (10.0 vs. 26.8, mean difference = 16.8, 95% confidence interval [CI] = 15.4 to 18.2, p < 0.001) after the implementation of APL. Procedures logged with the APL system were more complete (76% vs. 100%, p < 0.001) and more accurate (87% vs. 99%, p < 0.001). Most residents (42/48, 88%) used APL to log at least 90% of procedures. Only 4% of procedures eligible for automation were logged manually in the post-APL period.There was a significant increase in the daily mean number of procedures logged after the implementation of APL. Recorded data were more complete and more accurate during this time frame. This innovative system improved resident logging of required procedures and helped our assessment of Accreditation Council for Graduate Medical Education (ACGME) Patient Care and Practice-Based Learning Competencies for individual residents.
The strategy of relying solely on current SARS-CoV-2 vaccines to halt SARS-CoV-2 transmission has proven infeasible. In response, many public-health authorities have advocated for using vaccines to limit mortality while permitting unchecked SARS-CoV-2 spread (“learning to live with the disease”). The feasibility of this strategy critically depends on the infection fatality rate (IFR) of SARS-CoV-2. An expectation exists that the IFR will decrease due to selection against virulence. In this work, we perform a viral fitness estimation to examine the basis for this expectation. Our findings suggest large increases in virulence for SARS-CoV-2 would result in minimal loss of transmissibility, implying that the IFR may vary freely under neutral evolutionary drift. We use an SEIRS model framework to examine the effect of hypothetical changes in the IFR on steady-state death tolls under COVID-19 endemicity. Our modeling suggests that endemic SARS-CoV-2 implies vast transmission resulting in yearly US COVID-19 death tolls numbering in the hundreds of thousands under many plausible scenarios, with even modest increases in the IFR leading to unsustainable mortality burdens. Our findings highlight the importance of enacting a concerted strategy and continued development of biomedical interventions to suppress SARS-CoV-2 transmission and slow its evolution.
In household contact investigations of tuberculosis (TB), a second tuberculin skin test (TST) obtained several weeks after a first negative result consistently identifies individuals that undergo TST conversion. It remains unclear whether this delay in M. tuberculosis infection is related to differences in the infectious exposure, TST boosting, partial host resistance, or some other factor. We conducted a household contact study Vitória, Brazil. Between 2008 and 2013, we identified culture-positive pulmonary TB patients and evaluated their household contacts with both a TST and interferon gamma release assay (IGRA), and identified TST converters at 8–12 weeks post study enrollment. Contacts were classified as TST-positive (≥10 mm) at baseline, TST converters, or persistently TST-negative. We compared TST converters to TST-positive and to TST-negative contacts separately, using generalized estimating equations. We enrolled 160 index patients and 838 contacts; 523 (62.4%) were TST+, 62 (7.4%) TST converters, and 253 (30.2%) TST−. TST converters were frequently IGRA− at 8–12 weeks. In adjusted analyses, characteristics distinguishing TST converters from TST+ contacts (no contact with another TB patient and residence ownership) were different than those differentiating them from TST− contacts (stronger cough in index patient and contact BCG scar). The individual risk and timing of M. tuberculosis infection within households is variable and dependent on index patient, contact and environmental factors within the household, and the surrounding community. Our findings suggest a threshold effect in the risk of infection in humans.
As the COVID-19 pandemic drags into its second year, there is hope on the horizon, in the form of SARS-CoV-2 vaccines which promise disease suppression and a return to pre-pandemic normalcy. In this study we critically examine the basis for that hope, using an epidemiological modeling framework to establish the link between vaccine characteristics and effectiveness in bringing an end to this unprecedented public health crisis. Our findings suggest that a return to pre-pandemic social and economic conditions without fully suppressing SARS-CoV-2 will lead to extensive viral spread, resulting in a high disease burden even in the presence of vaccines that reduce risk of infection and mortality. Our modeling points to the feasibility of complete SARS-CoV-2 suppression with high population-level compliance and vaccines that are highly effective at reducing SARS-CoV-2 infection. Notably, vaccine-mediated reduction of transmission is critical for viral suppression, and in order for partially-effective vaccines to play a positive role in SARS-CoV-2 suppression, complementary biomedical interventions and public health measures must be deployed simultaneously.
Contact tracing forms a crucial part of the public-health toolbox in mitigating and understanding emergent pathogens and nascent disease outbreaks. Contact tracing in the United States was conducted during the pre-Omicron phase of the ongoing COVID-19 pandemic. This tracing relied on voluntary reporting and responses, often using rapid antigen tests due to lack of accessibility to PCR tests. These limitations, combined with SARS-CoV-2's propensity for asymptomatic transmission, raise the question "how reliable was contact tracing for COVID-19 in the United States"? We answered this question using a Markov model to examine the efficiency with which transmission could be detected based on the design and response rates of contact tracing studies in the United States. Our results suggest that contact tracing protocols in the U.S. are unlikely to have identified more than 1.65% (95% uncertainty interval: 1.62-1.68%) of transmission events with PCR testing and 1.00% (95% uncertainty interval 0.98-1.02%) with rapid antigen testing. When considering a more robust contact tracing scenario, based on compliance rates in East Asia with PCR testing, this increases to 62.7% (95% uncertainty interval: 62.6-62.8%). We did not assume presence of asymptomatic transmission or superspreading, making our estimates upper bounds on the actual percentages traced. These findings highlight the limitations in interpretability for studies of SARS-CoV-2 disease spread based on U.S. contact tracing and underscore the vulnerability of the population to future disease outbreaks, for SARS-CoV-2 and other pathogens.
Household contacts of pulmonary tuberculosis (TB) patients are at increased risk of TB infection and disease. However, their risk in relation to the intensity of exposure remains unknown.We studied smear-positive TB cases and their household contacts in Vitória, Brazil. We collected clinical, demographic and radiographic information from TB cases, and obtained tuberculin skin test (TST) and QuantiFERON-TB Gold (QFT) results from household contacts. We measured intensity of exposure using a proximity score and sleep location in relation to the TB index case and defined infection by TST ≥10 mm or QFT ≥0.35 UI·mL-1 We ascertained secondary TB cases by reviewing local and nationwide case registries.We included 160 TB index cases and 894 household contacts. 464 (65%) had TB infection and 23 (2.6%) developed TB disease. Risk of TB infection and disease increased with more intense exposures. In an adjusted analysis, the proximity score was associated with TB disease (OR 1.61, 95% CI 1.25-2.08; p<0.000); however, its diagnostic performance was only moderate.Intensity of exposure increased risk of TB infection and disease among household contacts; however, its diagnostic performance was still suboptimal. A biomarker to target preventive therapy is urgently needed in this at-risk population.
In the face of a long-running pandemic, understanding the drivers of ongoing SARS-CoV-2 transmission is crucial for the rational management of COVID-19 disease burden. Keeping schools open has emerged as a vital societal imperative during the pandemic, but in-school transmission of SARS-CoV-2 can contribute to further prolonging the pandemic. In this context, the role of schools in driving SARS-CoV-2 transmission acquires critical importance. Here we model in-school transmission from first principles to investigate the effectiveness of layered mitigation strategies on limiting in-school spread. We examined the effect of masks and air quality (ventilation, filtration and ionizers) on steady-state viral load in classrooms, as well as on the number of particles inhaled by an uninfected person. The effectiveness of these measures in limiting viral transmission was assessed for variants with different levels of mean viral load (ancestral, Delta, Omicron). Our results suggest that a layered mitigation strategy can be used effectively to limit in-school transmission, with certain limitations. First, poorly designed strategies (insufficient ventilation, no masks, staying open under high levels of community transmission) will permit in-school spread even if some level of mitigation is present. Second, for viral variants that are sufficiently contagious, it may be difficult to construct any set of interventions capable of blocking transmission once an infected individual is present, underscoring the importance of other measures. Our findings provide practical recommendations; in particular, the use of a layered mitigation strategy that is designed to limit transmission, with other measures such as frequent surveillance testing and smaller class sizes (such as by offering remote schooling options to those who prefer it) as needed.
