The role of socio-economic disparities in the relative success and persistence of SARS-CoV-2 variants in New York City in early 2021.

Socio-economic disparities were associated with disproportionate viral incidence between neighborhoods of New York City (NYC) during the first wave of SARS-CoV-2. We investigated how these disparities affected the co-circulation of SARS-CoV-2 variants during the second wave in NYC. We tested for correlation between the prevalence, in late 2020/early 2021, of Alpha, Iota, Iota with E484K mutation (Iota-E484K), and B.1-like genomes and pre-existing immunity (seropositivity) in NYC neighborhoods. In the context of varying seroprevalence we described socio-economic profiles of neighborhoods and performed migration and lineage persistence analyses using a Bayesian phylogeographical framework. Seropositivity was greater in areas with high poverty and a larger proportion of Black and Hispanic or Latino residents. Seropositivity was positively correlated with the proportion of Iota-E484K and Iota genomes, and negatively correlated with the proportion of Alpha and B.1-like genomes. The proportion of persisting Alpha lineages declined over time in locations with high seroprevalence, whereas the proportion of persisting Iota-E484K lineages remained the same in high seroprevalence areas. During the second wave, the geographic variation of standing immunity, due to disproportionate disease burden during the first wave of SARS-CoV-2 in NYC, allowed for the immune evasive Iota-E484K variant, but not the more transmissible Alpha variant, to circulate in locations with high pre-existing immunity.

Poorly Controlled Diabetes in New York City: Mapping High-Density Neighborhoods.

OBJECTIVE: To identify geographic areas in New York City (NYC) for implementing programming focused on reducing the burden attributed to poor glycemic control and improving the health of New Yorkers. DESIGN: We geocoded addresses of NYC residents in the NYC Hemoglobin A1c (HbA1C) Registry with high (>9%) HbA1c test values from 2011 to 2013 on an NYC base map. The ArcGIS point density spatial analysis tool was applied to create a map of NYC residents with diabetes in poor glycemic control. SETTING: The setting for HbA1c testing was medical facilities within NYC. PARTICIPANTS: The study population included NYC residents (excluding undomiciled persons and addresses corresponding to prisons, hospitals, or nursing homes) 18 years or older who underwent HbA1c testing from 2011 to 2013. MAIN OUTCOME MEASURES: A map depicting point density of NYC residents with poor glycemic control was developed each year from 2011 to 2013 (2011: n = 70 359; 2012: n = 75 643; 2013: n = 78 694). RESULTS: Particularly, high densities of persons in poor glycemic control were identified in Flatbush, East Harlem, Washington Heights/Inwood, and the South Bronx. The 2 highest-density gradients (out of 9) covered approximately 1.7% of the total habitable area in NYC, while accounting for more than 1 in 10 (10.5%) persons in poor glycemic control. The 3 highest-density gradients covered 4.1% of NYC's habitable area and accounted for more than 1 in 5 (21.9%) persons in poor glycemic control. CONCLUSION: The point density analysis highlighted several defined geographic areas representing a meaningful proportion of the population in poor glycemic control. This analysis could be used to raise community awareness and guide potential programming focused on reducing the burden of poor glycemic control such as the placement of diabetes self-management education classes, community health workers, and farmers' markets. Given the geographic breadth of NYC and limited resources, focused efforts on these defined areas would reach a sizeable number of the at-risk population.

Viruses associated with acute respiratory infections and influenza-like illness among outpatients from the Influenza Incidence Surveillance Project, 2010-2011.

BACKGROUND: The Influenza Incidence Surveillance Project (IISP) monitored outpatient acute respiratory infection (ARI; defined as the presence of ≥ 2 respiratory symptoms not meeting ILI criteria) and influenza-like illness (ILI) to determine the incidence and contribution of associated viral etiologies. METHODS: From August 2010 through July 2011, 57 outpatient healthcare providers in 12 US sites reported weekly the number of visits for ILI and ARI and collected respiratory specimens on a subset for viral testing. The incidence was estimated using the number of patients in the practice as the denominator, and the virus-specific incidence of clinic visits was extrapolated from the proportion of patients testing positive. RESULTS: The age-adjusted cumulative incidence of outpatient visits for ARI and ILI combined was 95/1000 persons, with a viral etiology identified in 58% of specimens. Most frequently detected were rhinoviruses/enteroviruses (RV/EV) (21%) and influenza viruses (21%); the resulting extrapolated incidence of outpatient visits was 20 and 19/1000 persons respectively. The incidence of influenza virus-associated clinic visits was highest among patients aged 2-17 years, whereas other viruses had varied patterns among age groups. CONCLUSIONS: The IISP provides a unique opportunity to estimate the outpatient respiratory illness burden by etiology. Influenza virus infection and RV/EV infection(s) represent a substantial burden of respiratory disease in the US outpatient setting, particularly among children.

Study of electronic prescribing rates and barriers identified among providers using electronic health records in New York City.

BACKGROUND: Increased electronic prescribing (eRx) rates have the potential to prevent errors, increase patient safety, and curtail fraud. US Federal meaningful use guidelines require at least a 40% electronic prescribing rate. OBJECTIVE: We evaluated eRx rates among primary care providers in New York City in order to determine trends as well as identify any obstacles to increased eRx rates required by meaningful use guidelines. METHODS: The data we analysed included automatic electronic data transmissions from providers enrolled in the Primary Care Information Project (PCIP) from 1 January 2009 to 1 July 2010 and follow-up telephone calls to a subset of these providers to identify potential barriers to increased eRx usage. RESULTS: Over the course of the study, these providers increased the eRx rate from 12.9 to 27.5%, with an average rate of 24.1%. Conversations with providers identified their perceived barriers to increased eRx use as primarily patient preference for paper prescriptions and a belief that many pharmacies do not accept eRx. CONCLUSIONS: The data gathered from our providers indicate that there is an increasing trend in the eRx rate to 27.5% by July 2010, but still short of the 40% meaningful use level. However, obstacles to increased rates remain primarily providers' belief that many patients prefer paper prescriptions and many pharmacies are not yet prepared to accept electronic prescriptions.

Detection and characterization of the SARS-CoV-2 lineage B.1.526 in New York.

Wide-scale SARS-CoV-2 genome sequencing is critical to tracking viral evolution during the ongoing pandemic. We develop the software tool, Variant Database (VDB), for quickly examining the changing landscape of spike mutations. Using VDB, we detect an emerging lineage of SARS-CoV-2 in the New York region that shares mutations with previously reported variants. The most common sets of spike mutations in this lineage (now designated as B.1.526) are L5F, T95I, D253G, E484K or S477N, D614G, and A701V. This lineage was first sequenced in late November 2020. Phylodynamic inference confirmed the rapid growth of the B.1.526 lineage. In concert with other variants, like B.1.1.7, the rise of B.1.526 appears to have extended the duration of the second wave of COVID-19 cases in NYC in early 2021. Pseudovirus neutralization experiments demonstrated that B.1.526 spike mutations adversely affect the neutralization titer of convalescent and vaccinee plasma, supporting the public health relevance of this lineage.

Detection and characterization of the SARS-CoV-2 lineage B.1.526 in New York.

Wide-scale SARS-CoV-2 genome sequencing is critical to tracking viral evolution during the ongoing pandemic. Variants first detected in the United Kingdom, South Africa, and Brazil have spread to multiple countries. We developed the software tool, Variant Database (VDB), for quickly examining the changing landscape of spike mutations. Using VDB, we detected an emerging lineage of SARS-CoV-2 in the New York region that shares mutations with previously reported variants. The most common sets of spike mutations in this lineage (now designated as B.1.526) are L5F, T95I, D253G, E484K or S477N, D614G, and A701V. This lineage was first sequenced in late November 2020 when it represented <1% of sequenced coronavirus genomes that were collected in New York City (NYC). By February 2021, genomes from this lineage accounted for ~32% of 3288 sequenced genomes from NYC specimens. Phylodynamic inference confirmed the rapid growth of the B.1.526 lineage in NYC, notably the sub-clade defined by the spike mutation E484K, which has outpaced the growth of other variants in NYC. Pseudovirus neutralization experiments demonstrated that B.1.526 spike mutations adversely affect the neutralization titer of convalescent and vaccinee plasma, indicating the public health importance of this lineage.

Comparing the partitioning behavior of Giardia and Cryptosporidium with that of indicator organisms in stormwater runoff.

Microbial association with particles can significantly affect the fate and transport characteristics of microbes in aquatic systems as particle-associated organisms will be less mobile in the environment than their free phase (i.e. unattached) counterparts. As such, similarities or dissimilarities in the partitioning behavior of indicator organisms and pathogens may have an impact on the suitability of a particular indicator to act as a surrogate for a pathogen. This research analyzed the partitioning behavior of two pathogens (Cryptosporidium, Giardia) and several common indicator organisms (fecal coliform, Escherichia coli, Enterococci, Clostridium perfringens spores, and coliphage) in natural waters under both dry and wet weather conditions. Samples were taken from several streams in two distinct sampling phases: (i) single grab samples; and (ii) intrastorm samples obtained throughout the duration of four storms. Partitioning behavior varied by microbial type, with 15-30% of bacterial indicators (fecal coliform, E. coli, and Enterococci) associated with settleable particles compared to 50% for C. perfringens spores. Both pathogens exhibited similar levels of particle association during dry weather (roughly 30%), with increased levels observed during wet weather events (Giardia to 60% and Cryptosporidium to 40%). The settling velocities of particle-associated microbes were also estimated, with those of the bacterial indicators (fecal coliform, E. coli, and Enterococci), as well as C. perfringens spores, being similar to that of the Giardia and Cryptosporidium, suggesting these organisms may exhibit similar transport behavior. With respect to intrastorm analysis, the highest microbial concentrations, in both particle-associated and free phase, occurred during the earlier stages of a storm. The total loadings of both indicators and pathogens were also estimated over the course of individual storms.

Comparison of outpatient medically attended and community-level influenza-like illness-New York City, 2013-2015.

BACKGROUND: Surveillance of influenza-like illness (ILI) in the United States is primarily conducted through medical settings despite a significant burden of non-medically attended ILI. OBJECTIVES: To assess consistency between surveillance for respiratory viruses in outpatient and community settings using ILI surveillance from the Centers for Disease Control and Prevention Influenza Incidence Surveillance Project (IISP) and the Mobile Surveillance for Acute Respiratory Infections (ARI) and Influenza-Like Illness in the Community (MoSAIC) Study. METHODS: The Influenza Incidence Surveillance Project conducts ILI surveillance in 3 primary care clinics in New York City, and MoSAIC conducts community-based ILI/ARI surveillance through text messaging among a cohort of New York City residents. Both systems obtain respiratory specimens from participants with ILI/ARI and test for multiple pathogens. We conducted a retrospective review of ILI cases in IISP and MoSAIC from January 2013 to May 2015 with descriptive analyses of clinical and laboratory data. RESULTS: Five-hundred twelve MoSAIC and 669 IISP participants met an ILI criteria (fever with cough or sore throat) and were included. Forty percent of MoSAIC participants sought care; the majority primary care. Pathogens were detected in 63% of MoSAIC and 70% of IISP cases. The relative distribution of influenza and other respiratory viruses detected was similar; however, there were statistically significant differences in the frequency that were not explained by care seeking. CONCLUSIONS: Outpatient and community-based surveillance in the one found similar timing and relative distribution of respiratory viruses, but community surveillance in a single neighborhood may not fully capture the variations in ILI etiology that occur more broadly.