Ecological countermeasures to prevent pathogen spillover and subsequent pandemics.

Substantial global attention is focused on how to reduce the risk of future pandemics. Reducing this risk requires investment in prevention, preparedness, and response. Although preparedness and response have received significant focus, prevention, especially the prevention of zoonotic spillover, remains largely absent from global conversations. This oversight is due in part to the lack of a clear definition of prevention and lack of guidance on how to achieve it. To address this gap, we elucidate the mechanisms linking environmental change and zoonotic spillover using spillover of viruses from bats as a case study. We identify ecological interventions that can disrupt these spillover mechanisms and propose policy frameworks for their implementation. Recognizing that pandemics originate in ecological systems, we advocate for integrating ecological approaches alongside biomedical approaches in a comprehensive and balanced pandemic prevention strategy.

Evaluating completion rates of COVID-19 contact tracing surveys in New York City.

IMPORTANCE: Contact tracing is the process of identifying people who have recently been in contact with someone diagnosed with an infectious disease. During an outbreak, data collected from contact tracing can inform interventions to reduce the spread of infectious diseases. Understanding factors associated with completion rates of contact tracing surveys can help design improved interview protocols for ongoing and future programs. OBJECTIVE: To identify factors associated with completion rates of COVID-19 contact tracing surveys in New York City (NYC) and evaluate the utility of a predictive model to improve completion rates, we analyze laboratory-confirmed and probable COVID-19 cases and their self-reported contacts in NYC from October 1st 2020 to May 10th 2021. METHODS: We analyzed 742,807 case investigation calls made during the study period. Using a log-binomial regression model, we examined the impact of age, time of day of phone call, and zip code-level demographic and socioeconomic factors on interview completion rates. We further developed a random forest model to predict the best phone call time and performed a counterfactual analysis to evaluate the change of completion rates if the predicative model were used. RESULTS: The percentage of contact tracing surveys that were completed was 79.4%, with substantial variations across ZIP code areas. Using a log-binomial regression model, we found that the age of index case (an individual who has tested positive through PCR or antigen testing and is thus subjected to a case investigation) had a significant effect on the completion of case investigation - compared with young adults (the reference group,24 years old < age < = 65 years old), the completion rate for seniors (age > 65 years old) were lower by 12.1% (95%CI: 11.1% - 13.3%), and the completion rate for youth group (age < = 24 years old) were lower by 1.6% (95%CI: 0.6% -2.6%). In addition, phone calls made from 6 to 9 pm had a 4.1% (95% CI: 1.8% - 6.3%) higher completion rate compared with the reference group of phone calls attempted from 12 and 3 pm. We further used a random forest algorithm to assess its potential utility for selecting the time of day of phone call. In counterfactual simulations, the overall completion rate in NYC was marginally improved by 1.2%; however, certain ZIP code areas had improvements up to 7.8%. CONCLUSION: These findings suggest that age and time of day of phone call were associated with completion rates of case investigations. It is possible to develop predictive models to estimate better phone call time for improving completion rates in certain communities.

Community transmission of SARS-CoV-2 during the Delta wave in New York City.

BACKGROUND: Understanding community transmission of SARS-CoV-2 variants of concern (VOCs) is critical for disease control in the post pandemic era. The Delta variant (B.1.617.2) emerged in late 2020 and became the dominant VOC globally in the summer of 2021. While the epidemiological features of the Delta variant have been extensively studied, how those characteristics shaped community transmission in urban settings remains poorly understood. METHODS: Using high-resolution contact tracing data and testing records, we analyze the transmission of SARS-CoV-2 during the Delta wave within New York City (NYC) from May 2021 to October 2021. We reconstruct transmission networks at the individual level and across 177 ZIP code areas, examine network structure and spatial spread patterns, and use statistical analysis to estimate the effects of factors associated with COVID-19 spread. RESULTS: We find considerable individual variations in reported contacts and secondary infections, consistent with the pre-Delta period. Compared with earlier waves, Delta-period has more frequent long-range transmission events across ZIP codes. Using socioeconomic, mobility and COVID-19 surveillance data at the ZIP code level, we find that a larger number of cumulative cases in a ZIP code area is associated with reduced within- and cross-ZIP code transmission and the number of visitors to each ZIP code is positively associated with the number of non-household infections identified through contact tracing and testing. CONCLUSIONS: The Delta variant produced greater long-range spatial transmission across NYC ZIP code areas, likely caused by its increased transmissibility and elevated human mobility during the study period. Our findings highlight the potential role of population immunity in reducing transmission of VOCs. Quantifying variability of immunity is critical for identifying subpopulations susceptible to future VOCs. In addition, non-pharmaceutical interventions limiting human mobility likely reduced SARS-CoV-2 spread over successive pandemic waves and should be encouraged for reducing transmission of future VOCs.

Integrating Contact Tracers Into Point-of-Care Testing Workflow to Accelerate the Tracing of People With Exposure to COVID-19, August-December 2020, New York City.

OBJECTIVES: We assessed the timeliness of contact tracing following rapid-positive COVID-19 test result at point-of-care testing (POCT) sites in New York City (NYC). DESIGN: Interviewed case-patients to elicit exposed contacts and conducted COVID-19 exposure notifications. SETTINGS: Twenty-two COVID-19 POCT sites in NYC, the 2 NYC international airports, and 1 ferry terminal. PARTICIPANTS: Case-patients with rapid-positive COVID-19 test results and their named contacts. MAIN OUTCOME MEASURES: We quantified the proportions of interviewed individuals with COVID-19 and notified contacts and assessed the timeliness between the dates of the rapid-positive COVID-19 test results and the interviews or notifications. RESULTS: In total, 11 683 individuals with rapid-positive COVID-19 test results were referred for contact tracing on the day of their diagnosis; 8878 (76) of whom were interviewed within 1 day of diagnosis, of whom 5499 (62%) named 11 486 contacts. A median of 1.24 contacts were identified from each interview. The odds of eliciting contacts were significantly higher among individuals reporting COVID-19 symptoms than among persons with no symptoms (51% vs 36%; adjusted odds ratio [aOR] = 1.37; 95% confidence interval [CI], 1.11-1.70) or living with 1 or more persons than living alone (89% vs 38%; aOR = 12.11; 95% CI, 10.73-13.68). Among the 8878 interviewed case-patients, 8317 (94%) were interviewed within 1 day of their rapid-positive COVID-19 test results and 91% of contact notifications were completed within 1 day of contact identification. The median interval from test result to interview date and from case investigation interview to contact notification were both 0 days (IQR = 0). CONCLUSIONS: The integration of contact tracers into COVID-19 POCT workflow achieved timely case investigation and contact notification. Accelerated contact tracing can be used to curb COVID-19 transmission during local outbreaks.

Interventions to Reduce Risk for Pathogen Spillover and Early Disease Spread to Prevent Outbreaks, Epidemics, and Pandemics.

The pathogens that cause most emerging infectious diseases in humans originate in animals, particularly wildlife, and then spill over into humans. The accelerating frequency with which humans and domestic animals encounter wildlife because of activities such as land-use change, animal husbandry, and markets and trade in live wildlife has created growing opportunities for pathogen spillover. The risk of pathogen spillover and early disease spread among domestic animals and humans, however, can be reduced by stopping the clearing and degradation of tropical and subtropical forests, improving health and economic security of communities living in emerging infectious disease hotspots, enhancing biosecurity in animal husbandry, shutting down or strictly regulating wildlife markets and trade, and expanding pathogen surveillance. We summarize expert opinions on how to implement these goals to prevent outbreaks, epidemics, and pandemics.

COVID-19 Case Investigation and Contact Tracing in New York City, June 1, 2020, to October 31, 2021.

Importance: Contact tracing is a core strategy for preventing the spread of many infectious diseases of public health concern. Better understanding of the outcomes of contact tracing for COVID-19 as well as the operational opportunities and challenges in establishing a program for a jurisdiction as large as New York City (NYC) is important for the evaluation of this strategy. Objective: To describe the establishment, scaling, and maintenance of Trace, NYC's contact tracing program, and share data on outcomes during its first 17 months. Design, Setting, and Participants: This cross-sectional study included people with laboratory test-confirmed and probable COVID-19 and their contacts in NYC between June 1, 2020, and October 31, 2021. Trace launched on June 1, 2020, and had a workforce of 4147 contact tracers, with the majority of the workforce performing their jobs completely remotely. Data were analyzed in March 2022. Main Outcomes and Measures: Number and proportion of persons with COVID-19 and contacts on whom investigations were attempted and completed; timeliness of interviews relative to symptom onset or exposure for symptomatic cases and contacts, respectively. Results: Case investigations were attempted for 941 035 persons. Of those, 840 922 (89.4%) were reached and 711 353 (75.6%) completed an intake interview (women and girls, 358 775 [50.4%]; 60 178 [8.5%] Asian, 110 636 [15.6%] Black, 210 489 [28.3%] Hispanic or Latino, 157 349 [22.1%] White). Interviews were attempted for 1 218 650 contacts. Of those, 904 927 (74.3%) were reached, and 590 333 (48.4%) completed intake (women and girls, 219 261 [37.2%]; 47 403 [8.0%] Asian, 98 916 [16.8%] Black, 177 600 [30.1%] Hispanic or Latino, 116 559 [19.7%] White). Completion rates were consistent over time and resistant to changes related to vaccination as well as isolation and quarantine guidance. Among symptomatic cases, median time from symptom onset to intake completion was 4.7 days; a median 1.4 contacts were identified per case. Median time from contacts' last date of exposure to intake completion was 2.3 days. Among contacts, 30.1% were tested within 14 days of notification. Among cases, 27.8% were known to Trace as contacts. The overall expense for Trace from May 6, 2020, through October 31, 2021, was approximately $600 million. Conclusions and Relevance: Despite the complexity of developing a contact tracing program in a diverse city with a population of over 8 million people, in this case study we were able to identify 1.4 contacts per case and offer resources to safely isolate and quarantine to over 1 million cases and contacts in this study period.

Outcomes of a Community Engagement and Information Gathering Program to Support Telephone-Based COVID-19 Contact Tracing: Descriptive Analysis.

BACKGROUND: Contact tracing is an important public health tool for curbing the spread of infectious diseases. Effective and efficient contact tracing involves the rapid identification of individuals with infection and their exposed contacts and ensuring their isolation or quarantine, respectively. Manual contact tracing via telephone call and digital proximity app technology have been key strategies in mitigating the spread of COVID-19. However, many people are not reached for COVID-19 contact tracing due to missing telephone numbers or nonresponse to telephone calls. The New York City COVID-19 Trace program augmented the efforts of telephone-based contact tracers with information gatherers (IGs) to search and obtain telephone numbers or residential addresses, and community engagement specialists (CESs) made home visits to individuals that were not contacted via telephone calls. OBJECTIVE: The aim of this study was to assess the contribution of information gathering and home visits to the yields of COVID-19 contact tracing in New York City. METHODS: IGs looked for phone numbers or addresses when records were missing phone numbers to locate case-patients or contacts. CESs made home visits to case-patients and contacts with no phone numbers or those who were not reached by telephone-based tracers. Contact tracing management software was used to triage and queue assignments for the telephone-based tracers, IGs, and CESs. We measured the outcomes of contact tracing-related tasks performed by the IGs and CESs from July 2020 to June 2021. RESULTS: Of 659,484 cases and 861,566 contact records in the Trace system, 28% (185,485) of cases and 35% (303,550) of contacts were referred to IGs. IGs obtained new phone numbers for 33% (61,804) of case-patients and 11% (31,951) of contacts; 50% (31,019) of the case-patients and 46% (14,604) of the contacts with new phone numbers completed interviews; 25% (167,815) of case-patients and 8% (72,437) of contacts were referred to CESs. CESs attempted 80% (132,781) of case and 69% (49,846) of contact investigations, of which 47% (62,733) and 50% (25,015) respectively, completed interviews. An additional 12,192 contacts were identified following IG investigations and 13,507 following CES interventions. CONCLUSIONS: Gathering new or missing locating information and making home visits increased the number of case-patients and contacts interviewed for contact tracing and resulted in additional contacts. When possible, contact tracing programs should add information gathering and home visiting strategies to increase COVID-19 contact tracing coverage and yields as well as promote equity in the delivery of this public health intervention.

Community-Based Workforce for COVID-19 Contact Tracing and Prevention Activities in New York City, July-December 2020.

OBJECTIVES: High rates of hospitalization and death disproportionately affected Black, Latino, and Asian residents of New York City at the beginning of the COVID-19 pandemic. To suppress COVID-19 transmission, New York City implemented a workforce of community engagement specialists (CESs) to conduct home-based contact tracing when telephone numbers were lacking or telephone-based efforts were unsuccessful and to disseminate COVID-19 information and sanitary supplies. MATERIALS AND METHODS: We describe the recruitment, training, and deployment of a multilingual CES workforce with diverse sociodemographic backgrounds during July-December 2020 in New York City. We developed standard operating procedures for infection control and safety measures, procured supplies and means of transportation, and developed protocols and algorithms to efficiently distribute workload. RESULTS: From July through December 2020, 519 CESs were trained to conduct in-person contact tracing and activities in community settings, including homes, schools, and businesses, where they disseminated educational materials, face masks, hand sanitizer, and home-based specimen collection kits. During the study period, 94 704 records of people with COVID-19 and 61 246 contacts not reached by telephone-based contact tracers were referred to CESs. CESs attempted home visits or telephone calls with 84 230 people with COVID-19 and 49 303 contacts, reaching approximately 55 592 (66%) and 35 005 (71%), respectively. Other CES activities included monitoring recently arrived travelers under quarantine, eliciting contacts at point-of-care testing sites, and advising schools on school-based COVID-19 mitigation strategies. PRACTICE IMPLICATIONS: This diverse CES workforce allowed for safe, in-person implementation of contact tracing and other prevention services for individuals and communities impacted by COVID-19. This approach prioritized equitable delivery of community-based support services and resources.

Walking distance for vulnerable populations to public health emergency response points of dispensing in New York City.

During certain public health emergencies, points of dispensing (PODs) may be used to rapidly distribute medical countermeasures such as antibiotics to the general public to prevent disease. Jurisdictions across the country have identified sites for PODs in preparation for such an emergency; in New York City (NYC), the sites are identified based largely on population density. Vulnerable populations, defined for this analysis as persons with income below the federal poverty level, persons with less than a high school diploma, foreign-born persons, persons of color, persons aged ≥65 years, physically disabled persons, and unemployed persons, often experience a wide range of health inequities. In NYC, these populations are often concentrated in certain geographic areas and rely heavily on public transportation. Because public transportation will almost certainly be affected during large-scale public health emergencies that would require the rapid mass dispensing of medical countermeasures, we evaluated walking distances to PODs. We used an ordinary least squares (OLS) model and a geographically weighted regression (GWR) model to determine if certain characteristics that increase health inequities in the population are associated with longer distances to the nearest POD relative to the general NYC population. Our OLS model identified shorter walking distances to PODs in neighborhoods with a higher percentage of persons with income below the federal poverty level, higher percentage of foreign-born persons, or higher percentage of persons of color, and identified longer walking distances to PODs in neighborhoods with a higher percentage of persons with less than a high school diploma. Our GWR model confirmed the findings from the OLS model and further illustrated these patterns by certain neighborhoods. Our analysis shows that currently identified locations for PODs in NYC are generally serving vulnerable populations equitably-particularly those defined by race or income status-at least in terms of walking distance.

Hospital-level factors associated with death during pneumonia-associated hospitalization among adults-New York City, 2010-2014.

BACKGROUND: In New York City (NYC), pneumonia is a leading cause of death and most pneumonia deaths occur in hospitals. Whether the pneumonia death rate in NYC reflects reporting artifact or is associated with factors during pneumonia-associated hospitalization (PAH) is unknown. We aimed to identify hospital-level factors associated with higher than expected in-hospital pneumonia death rates among adults in NYC. METHODS: Data from January 1, 2010-December 31, 2014 were obtained from the New York Statewide Planning and Research Cooperative System and the American Hospital Association Database. In-hospital pneumonia standardized mortality ratio (SMR) was calculated for each hospital as observed PAH death rate divided by expected PAH death rate. To determine hospital-level factors associated with higher in-hospital pneumonia SMR, we fit a hospital-level multivariable negative binomial regression model. RESULTS: Of 148,172 PAH among adult NYC residents in 39 hospitals during 2010-2014, 20,820 (14.06%) resulted in in-hospital death. In-hospital pneumonia SMRs varied across NYC hospitals (0.77-1.23) after controlling for patient-level factors. An increase in average daily occupancy and membership in the Council of Teaching Hospitals were associated with increased in-hospital pneumonia SMR. CONCLUSIONS: Differences in in-hospital pneumonia SMRs between hospitals might reflect differences in disease severity, quality of care, or coding practices. More research is needed to understand the association between average daily occupancy and in-hospital pneumonia SMR. Additional pneumonia-specific training at teaching hospitals can be considered to address higher in-hospital pneumonia SMR in teaching hospitals.

Applying a One Health Approach in Global Health and Medicine: Enhancing Involvement of Medical Schools and Global Health Centers.

Background: Multidisciplinary and multisectoral approaches such as One Health and related concepts (e.g., Planetary Health, EcoHealth) offer opportunities for synergistic expertise to address complex health threats. The connections between humans, animals, and the environment necessitate collaboration among sectors to comprehensively understand and reduce risks and consequences on health and wellbeing. One Health approaches are increasingly emphasized for national and international plans and strategies related to zoonotic diseases, food safety, antimicrobial resistance, and climate change, but to date, the possible applications in clinical practice and benefits impacting human health are largely missing. Methods: In 2018 the "Application of the One Health Approach to Global Health Centers" conference held at the Albert Einstein College of Medicine convened experts involved in One Health policy and practice. The conference examined issues relevant to One Health approaches, sharing examples of challenges and successes to guide application to medical school curricula and clinical practice for human health. This paper presents a synthesis of conference proceedings, framed around objectives identified from presentations and audience feedback. Findings and Recommendations: The following objectives provide opportunities for One Health involvement and benefits for medical schools and global health centers by: 1) Improving One Health resource sharing in global health and medical education; 2) Creating pathways for information flow in clinical medicine and global health practice; 3) Developing innovative partnerships for improved health sector outcomes; and 4) Informing and empowering health through public outreach. These objectives can leverage existing resources to deliver value to additional settings and stakeholders through resource efficiency, more holistic and effective service delivery, and greater ability to manage determinants of poor health status. We encourage medical and global health educators, practitioners, and students to explore entry points where One Health can add value to their work from local to global scale.

Community-setting pneumonia-associated hospitalizations by level of urbanization-New York City versus other areas of New York State, 2010-2014.

BACKGROUND: New York City (NYC) reported a higher pneumonia and influenza death rate than the rest of New York State during 2010-2014. Most NYC pneumonia and influenza deaths are attributed to pneumonia caused by infection acquired in the community, and these deaths typically occur in hospitals. METHODS: We identified hospitalizations of New York State residents aged ≥20 years discharged from New York State hospitals during 2010-2014 with a principal diagnosis of community-setting pneumonia or a secondary diagnosis of community-setting pneumonia if the principal diagnosis was respiratory failure or sepsis. We examined mean annual age-adjusted community-setting pneumonia-associated hospitalization (CSPAH) rates and proportion of CSPAH with in-hospital death, overall and by sociodemographic group, and produced a multivariable negative binomial model to assess hospitalization rate ratios. RESULTS: Compared with non-NYC urban, suburban, and rural areas of New York State, NYC had the highest mean annual age-adjusted CSPAH rate at 475.3 per 100,000 population and the highest percentage of CSPAH with in-hospital death at 13.7%. NYC also had the highest proportion of CSPAH patients residing in higher-poverty-level areas. Adjusting for age, sex, and area-based poverty, NYC residents experienced 1.3 (95% confidence interval [CI], 1.2-1.4), non-NYC urban residents 1.4 (95% CI, 1.3-1.6), and suburban residents 1.2 (95% CI, 1.1-1.3) times the rate of CSPAH than rural residents. CONCLUSIONS: In New York State, NYC as well as other urban areas and suburban areas had higher rates of CSPAH than rural areas. Further research is needed into drivers of CSPAH deaths, which may be associated with poverty.

Erroneous Reporting of Deaths Attributed to Pneumonia and Influenza at 2 New York City Teaching Hospitals, 2013-2014.

OBJECTIVES: Cause-of-death information, reported by frontline clinicians after a patient's death, is an irreplaceable source of public health data. However, systematic bias in cause-of-death reporting can lead to over- or underestimation of deaths attributable to different causes. New York City consistently reports higher rates of deaths attributable to pneumonia and influenza than many other US cities and the country. We investigated systematic erroneous reporting as a possible explanation for this phenomenon. METHODS: We reviewed all deaths from 2 New York City hospitals during 2013-2014 in which pneumonia or influenza was reported as the underlying cause of death (n = 188), and we examined the association between erroneous reporting and multiple extrinsic factors that may influence cause-of-death reporting (patient demographic characteristics and medical comorbidities, time and hospital location of death, type of medical provider reporting the death, and availability of certain diagnostic information). RESULTS: Pneumonia was erroneously reported as the underlying cause of death in 163 (86.7%) reports. We identified heart disease and dementia as the more likely underlying cause of death in 21% and 17% of erroneously reported deaths attributable to pneumonia, respectively. We found no significant association between erroneous reporting and the multiple extrinsic factors examined. CONCLUSIONS: Our results underscore how erroneous reporting of 1 condition can lead to underreporting of other causes of death. Misapplication or misunderstanding of procedures by medical providers, rather than extrinsic factors influencing the reporting process, are key drivers of erroneous cause-of-death reporting.

Infectious Disease Hospitalizations, New York City, 2001-2014.

OBJECTIVE: Hospital discharge data are a means of monitoring infectious diseases in a population. We investigated rates of infectious disease hospitalizations in New York City. METHODS: We analyzed data for residents discharged from New York State hospitals with a principal diagnosis of an infectious disease during 2001-2014 by using the Statewide Planning and Research Cooperative System. We calculated annual age-adjusted hospitalization rates and the percentage of hospitalizations in which in-hospital death occurred. We examined diagnoses by site of infection or sepsis and by pathogen type. RESULTS: During 2001-2014, the mean annual age-adjusted rate of infectious disease hospitalizations in New York City was 1661.6 (95% CI, 1659.2-1663.9) per 100 000 population; the mean annual age-adjusted hospitalization rate decreased from 2001-2003 to 2012-2014 (rate ratio = 0.9; 95% CI, 0.9-0.9). The percentage of in-hospital death during 2001-2014 was 5.9%. The diagnoses with the highest mean annual age-adjusted hospitalization rates among all sites of infection and sepsis diagnoses were the lower respiratory tract, followed by sepsis. From 2001-2003 to 2012-2014, the mean annual age-adjusted hospitalization rate per 100 000 population for HIV decreased from 123.1 (95% CI, 121.7-124.5) to 40.0 (95% CI, 39.2-40.7) and for tuberculosis decreased from 10.2 (95% CI, 9.8-10.6) to 4.6 (95% CI, 4.4-4.9). CONCLUSIONS: Although hospital discharge data are subject to limitations, particularly for tracking sepsis, lower respiratory tract infections and sepsis are important causes of infectious disease hospitalizations in New York City. Hospitalizations for HIV infection and tuberculosis appear to be declining.