Analysis of the Morbidity and Mortality of Severe Influenza Infection in Clark County, Nevada for the 2010-2011 Influenza Season

Throughout the duration of any influenza season, influenza strains have the ability to evolve through mutation causing alterations in virulence. These changes may result in severe illness or death among susceptible populations; therefore, it is important to closely monitor influenza-associated hospitalizations and deaths. The University of Nevada, Las Vegas in collaboration with the Southern Nevada Health District analyzed data from the hospitalized influenza morbidity and mortality surveillance project for Clark County for the 2010-2011 influenza season. Among the study population (N= 158): the influenza strain type was found to be significantly associated with deaths (n= 25), vaccination status was not found to be significantly associated with death among hospitalized patients, and transformed data showed no statistically significant difference in the mean length of hospital stay based on the influenza strain type. These results will help inform public health agencies of the impact of influenza-associated hospitalizations and deaths, and inform the design of future surveillance systems

Differences in disease reporting: an analysis of state reportable conditions and their relationship to the nationally notifiable conditions list

The basis of public health surveillance is the reporting of diseases and conditions to the health department by clinicians and laboratories. In the United States, over eighty diseases and conditions of national importance (e.g., tuberculosis, syphilis, and cancer) are included on the list of Nationally Notifiable Conditions (NNC) for submission to the Centers for Disease Control and Prevention (CDC) by the states. The legal basis for disease reporting is found at the state level, where inconsistent laws may differ in terms of which conditions are reportable and their reporting process. The process by which states require the reporting of NNCs has not been thoroughly described, and the potential bias introduced by different reporting requirements has not been evaluated. State reportable disease lists were collected from state health department websites, state laws, and published CDC annual summaries. A descriptive, cross-sectional analysis of the reporting requirements of all 50 states, Washington D.C. and New York City was conducted. Factors associated with the states (e.g., population, public health funding) were evaluated to determine if any were associated with having large number of NNCs on the state’s reportable lists. Factors associated with the conditions (e.g. being vaccine preventable or a bioterrorism agent) were evaluated to determine if any were associated with the inclusion on state reporting lists. Additionally, pediatric influenza mortality, lead poisoning, tuberculosis and Shiga toxin-producing Escherichia coli infections were selected for an in-depth analysis of state reporting requirements. States required 76% to 100% (mean 90%) of NNCs to be reported; only Louisiana required the reporting of all NNCs. No factors associated with the conditions were identified as having a significant association with being included on state reportable lists; only 43% of NNCs were reportable in all states. States used 28 different reporting timeframes and required reporting by 72 different types of reporters. Having a larger state population was associated with requiring a greater number of NNCs to be reported, but no linear relationship was identified. Detailed analysis of the selected conditions found that states did not follow national recommendations when setting state reporting criteria; the inclusion of a new condition on the NNC list is a reflection of reporting practices already established in states, and as such, is not an effective tool to change state reporting practices. NNC data is frequently used in policy making, funding, and program evaluation, and bias introduced by different state reporting practices may make data collected unreliable for these purposes. This study proposes a method for the standardization of reporting practices across states, allowing for the standardize collection and interpretation of NNC data

Antibiotic Resistance Patterns of Bacterial Isolates from Blood in San Francisco County, California, 1996-1999

Countywide antibiotic resistance patterns may provide additional information from that obtained from national sampling or individual hospitals. We reviewed susceptibility patterns of selected bacterial strains isolated from blood in San Francisco County from January 1996 to March 1999. We found substantial hospital-to-hospital variability in proportional resistance to antibiotics in multiple organisms. This variability was not correlated with hospital indices such as number of intensive care unit or total beds, annual admissions, or average length of stay. We also found a significant increase in methicillin-resistant Staphylococcus aureus, vancomycin-resistant Enterococcus, and proportional resistance to multiple antipseudomonal antibiotics. We describe the utility, difficulties, and limitations of countywide surveillance

Assessing Psychological Impact of COVID-19 among Parents of Children Returning to K-12 Schools: A U.S. Based Cross-Sectional Survey

Background and Purpose: While impacts of the pandemic on family well-being have been documented in the literature, little is known about the psychological challenges faced by children and their parents as schools reopen after mandated closures. Therefore, the purpose of this study was to determine if sending children back to in-person school impacts the mental health of parents and the perceived mental health of their children. Methods: This cross-sectional descriptive study recruited a nationally representative, non-probability sample of parents or guardians (n = 2100) of children attending grades K-12 in the United States (U.S.) through a 58-item web-based survey. The univariate, bivariate, and multivariate statistical tests were used to analyze the data. Results: The mean scores of parental Coronavirus anxiety and Coronavirus obsession were significantly different between race/ethnic groups of parents. Parents with children going to private schools had significantly higher mean scores for Coronavirus anxiety and obsession compared to parents whose children are attending public schools. Nearly 55% of parental Coronavirus anxiety was explained by the generalized anxiety, separation anxiety, child’s vulnerability to infection, and school type of the child. Similarly, 52% of parental Coronavirus obsession was explained by the generalized anxiety, separation anxiety, child’s vulnerability to infection, and social phobia of the children. Conclusions: The COVID-19 pandemic has a substantial impact on psychological well-being of parents and their school-going children. Findings of this study will inform policy makers in developing targeted interventions to address unique needs of families with school-going children

Barriers for Cervical Cancer Screening in Women Living with HIV: A Systematic Review

Cervical cancer is a prominent cancer in U.S. women caused primarily by the human papilloma virus and its incidence and mortality rates have decreased through screening programs. Certain barriers are perceived to be affecting the rates of cervical cancer screening among women living with HIV (WLWH). A systematic review was conducted to identify and summarize these barriers among WLWH nationwide. There is a need to increase awareness and education among WLWH. Public health programs and community-based interventions should target women of low SES and minority status while assessing the barriers among this population to improve cervical cancer screening rates

Assessing Psychological Impact of COVID-19 among Parents of Children Returning to K-12 Schools: A U.S. Based Cross-Sectional Survey

Background and Purpose: While impacts of the pandemic on family well-being have been documented in the literature, little is known about the psychological challenges faced by children and their parents as schools reopen after mandated closures. Therefore, the purpose of this study was to determine if sending children back to in-person school impacts the mental health of parents and the perceived mental health of their children. Methods: This cross-sectional descriptive study recruited a nationally representative, non-probability sample of parents or guardians (n = 2100) of children attending grades K-12 in the United States (U.S.) through a 58-item web-based survey. The univariate, bivariate, and multivariate statistical tests were used to analyze the data. Results: The mean scores of parental Coronavirus anxiety and Coronavirus obsession were significantly different between race/ethnic groups of parents. Parents with children going to private schools had significantly higher mean scores for Coronavirus anxiety and obsession compared to parents whose children are attending public schools. Nearly 55% of parental Coronavirus anxiety was explained by the generalized anxiety, separation anxiety, child’s vulnerability to infection, and school type of the child. Similarly, 52% of parental Coronavirus obsession was explained by the generalized anxiety, separation anxiety, child’s vulnerability to infection, and social phobia of the children. Conclusions: The COVID-19 pandemic has a substantial impact on psychological well-being of parents and their school-going children. Findings of this study will inform policy makers in developing targeted interventions to address unique needs of families with school-going children

Deploying nEmesis: Preventing Foodborne Illness by Data Mining Social Media

Foodborne illness afflicts 48 million people annually in the U.S. alone. Over 128,000 are hospitalized and 3,000 die from the infection. While preventable with proper food safety practices, the traditional restaurant inspection process has limited impact given the predictability and low frequency of inspections, and the dynamic nature of the kitchen environment. Despite this reality, the inspection process has remained largely unchanged for decades. CDC has even identified food safety as one of seven ”winnable battles”; however, progress to date has been limited. In this work, we demonstrate significant improvements in food safety by marrying AI and the standard inspection process. We apply machine learning to Twitter data, develop a system that automatically detects venues likely to pose a public health hazard, and demonstrate its efficacy in the Las Vegas metropolitan area in a double-blind experiment conducted over three months in collaboration with Nevada’s health department. By contrast, previous research in this domain has been limited to indirect correlative validation using only aggregate statistics. We show that adaptive inspection process is 64 percent more effective at identifying problematic venues than the current state of the art. If fully deployed, our approach could prevent over 9,000 cases of foodborne illness and 557 hospitalizations annually in Las Vegas alone. Additionally, adaptive inspections result in unexpected benefits, including the identification of venues lacking permits, contagious kitchen staff, and fewer customer complaints filed with the Las Vegas health department

Antibiotic resistance patterns of bacterial isolates from blood in San Francisco County, California, 1996-1999.

Countywide antibiotic resistance patterns may provide additional information from that obtained from national sampling or individual hospitals. We reviewed susceptibility patterns of selected bacterial strains isolated from blood in San Francisco County from January 1996 to March 1999. We found substantial hospital-to-hospital variability in proportional resistance to antibiotics in multiple organisms. This variability was not correlated with hospital indices such as number of intensive care unit or total beds, annual admissions, or average length of stay. We also found a significant increase in methicillin-resistant Staphylococcus aureus, vancomycin-resistant Enterococcus, and proportional resistance to multiple antipseudomonal antibiotics. We describe the utility, difficulties, and limitations of countywide surveillance

Identification of Non-Fatal Opioid Overdose Cases Using 9-1-1 Computer Assisted Dispatch and Prehospital Patient Clinical Record Variables.

Background: The current epidemic of opioid overdoses in the United States necessitates a robust public health and clinical response. We described patterns of non-fatal opioid overdoses (NFOODs) in a small western region using data from the 9-1-1 Computer Assisted Dispatch (CAD) record and electronic Patient Clinical Records (ePCR) completed by EMS responders. We determined whether CAD and ePCR variables could identify NFOOD cases in 9-1-1 data for intervention and surveillance efforts. Methods: We conducted a retrospective analysis of 1 year of 9-1-1 emergency medical CAD and ePCR (including naloxone administration) data from the sole EMS provider in the response area. Cases were identified based on clinician review of the ePCR, and categorized as definitive NFOOD, probable NFOOD, or non-OOD. Sensitivity, specificity, positive and negative predictive values (PPV and NPV) of the most prevalent CAD and ePCR variables were calculated. We used a machine learning technique-Random-Forests (RF) modeling-to optimize our ability to accurately predict NFOOD cases within census blocks. Results: Of 37,960 9-1-1 calls, clinical review identified 158 NFOOD cases (0.4%), of which 123 (77.8%) were definitive and 35 (22.2%) were probable cases. Overall, 106 (67.1%) received naloxone from the EMS responder at the scene. As a predictor of NFOOD, naloxone administration by paramedics had 67.1% sensitivity, 99.6% specificity, 44% PPV, and 99.9% NPV. Using CAD variables alone achieved a sensitivity of 36.7% and specificity of 99.7%. Combining ePCR variables with CAD variables increased the diagnostic accuracy with the best RF model yielding 75.9% sensitivity, 99.9% specificity, 71.4% PPV, and 99.9% NPV. Conclusion: CAD problem type variables and naloxone administration, used alone or in combination, had sub-optimal predictive accuracy. However, a Random Forests modeling approach improved accuracy of identification, which could foster improved surveillance and intervention efforts. We identified the set of NFOODs that EMS encountered in a year and may be useful for future surveillance efforts

Post-overdose interventions triggered by calling 911: Centering the perspectives of people who use drugs (PWUDs)

BackgroundOpioid overdose deaths have increased exponentially in the United States. Bystander response to opioid overdose ideally involves administering naloxone, providing rescue breathing, and calling 911 to summon emergency medical assistance. Recently in the US, public health and public safety agencies have begun seeking to use 911 calls as a method to identify and deliver post-overdose interventions to opioid overdose patients. Little is known about the opinions of PWUDs about the barriers, benefits, or potential harms of post-overdose interventions linked to the 911 system. We sought to understand the perspectives of PWUDs about a method for using 911 data to identify opioid overdose cases and trigger a post-overdose intervention.Methods and findingsWe conducted three focus groups with 11 PWUDs in 2018. Results are organized into 4 categories: willingness to call 911 (benefits and risks of calling), thoughts about a technique to identify opioid overdoses in 911 data (benefits and concerns), thoughts about the proposed post-overdose intervention (benefits and concerns), and recommendations for developing an ideal post-overdose intervention. For most participants, calling 911 was synonymous with "calling the police" and law enforcement-related fears were pervasive, limiting willingness to engage with the 911 system. The technique to identify opioid overdoses and the proposed post-overdose intervention were identified as potentially lifesaving, but the benefits were balanced by concerns related to law enforcement involvement, intervention timing, and risks to privacy/reputation. Nearly universally, participants wished for a way to summon emergency medical assistance without triggering a law enforcement response.ConclusionsThe fact that the 911 system in the US inextricably links emergency medical assistance with law enforcement response inherently problematizes calling 911 for PWUDs, and has implications for surveillance and intervention. It is imperative to center the perspectives of PWUDs when designing and implementing interventions that rely on the 911 system for activation