Preparing for the next outbreak: A review of indices measuring outbreak preparedness, vulnerability, and resilience.

The COVID-19 pandemic has highlighted the need for relevant metrics describing the resources and community attributes that affect the impact of communicable disease outbreaks. Such tools can help inform policy, assess change, and identify gaps to potentially reduce the negative outcomes of future outbreaks. The present review was designed to identify available indices to assess communicable disease outbreak preparedness, vulnerability, or resilience, including articles describing an index or scale developed to address disasters or emergencies which could be applied to addressing a future outbreak. This review assesses the landscape of indices available, with a particular focus on tools assessing local-level attributes. This systematic review yielded 59 unique indices applicable to assessing communicable disease outbreaks through the lens of preparedness, vulnerability, or resilience. However, despite the large number of tools identified, only 3 of these indices assessed factors at the local level and were generalizable to different types of outbreaks. Given the influence of local resources and community attributes on a wide range of communicable disease outcomes, there is a need for local-level tools that can be applied broadly to various types of outbreaks. Such tools should assess both current and long-term changes in outbreak preparedness with the intent to identify gaps, inform local-level decision makers, public policy, and future response to current and novel outbreaks.

Effect of ambient PM2.5 on healthcare utilisation for acute respiratory illness, Melbourne, Victoria, Australia, 2014-2019.

Ambient particulate matter (PM2.5) is an important component of natural and human-generated air pollution and a major contributor to the global burden of disease. Short-term effects of PM2.5 exposure on respiratory illness have been described but most evidence arises from high pollution settings. We used case-crossover methods to estimate effects of outdoor PM2.5 levels on emergency department (ED) presentations and hospital admissions for a range of acute respiratory illnesses and age groups in Melbourne, Australia from 2014-2019, with and without adjustment for other pollutants and weather conditions, using daily and one-week averaged lags. We estimated incidence rate ratios for a 10 µg/m3 increase in 7-day average ambient PM2.5 of 1.043 (95% confidence interval (CI): 1.000-1.089) on ED presentation and 1.013 (95% CI: 0.971-1.056) on hospital admissions for acute respiratory illnesses for patients of any age. We observed distinct temporal patterns in daily lag effect by disease. The largest effects on acute lower respiratory tract infection and asthma were observed in children. Ambient PM2.5 levels rarely exceeded standards in place at the time. Although uncertainty around most point estimates was relatively wide, these findings are most compatible with adverse health effects of ambient PM2.5 at levels below currently established Australian national standards.Implications: Understanding the health impacts of air pollution is important for setting air quality targets, as well as for informing robust health system planning. Adverse effects of exposure to outdoor fine particulate matter on human respiratory health have been consistently described. However, most studies have been done in higher-pollution settings. Further, many studies have assessed health effects in broad categories such as all-cause respiratory mortality or hospitalization, and thus lack the granularity to inform detailed health service planning. Our study aimed to estimate effects of outdoor fine particulate matter on emergency department (ED) presentations and hospital admissions for a range of acute respiratory illnesses and age groups in Melbourne, Australia, a city with relatively good air quality by international comparison. Our study estimated consistent effects on both ED presentations and hospital admissions compatible with distinct patterns of adverse health effects at levels at or below established Australian national (and many international) standards. These results will help to inform both air quality policy and public health policy in similar settings.

Spatial distribution of tuberculosis incidence in Los Angeles County.

BACKGROUND: In Los Angeles County, the tuberculosis (TB) disease incidence rate is seven times higher among non-U.S.-born persons than U.S.-born persons and varies by country of birth. But translating these findings into public health action requires more granular information, especially considering that Los Angeles County is more than 4000 mile2. Local public health authorities may benefit from data on which areas of the county are most affected, yet these data remain largely unreported in part because of limitations of sparse data. We aimed to describe the spatial distribution of TB disease incidence in Los Angeles County while addressing challenges arising from sparse data and accounting for known cofactors. METHODS: Data on 5447 TB cases from Los Angeles County were combined with stratified population estimates available from the 2005-2011 Public Use Microdata Survey. TB disease incidence rates stratified by country of birth and Public Use Microdata Area were calculated and spatial smoothing was applied using a conditional autoregressive model. We used Bayesian Poisson models to investigate spatial patterns adjusting for age, sex, country of birth and years since initial arrival in the U.S. RESULTS: There were notable differences in the crude and spatially-smoothed maps of TB disease rates for high-risk subgroups, namely persons born in Mexico, Vietnam or the Philippines. Spatially-smoothed maps showed areas of high incidence in downtown Los Angeles and surrounding areas for persons born in the Philippines or Vietnam. Areas of high incidence were more dispersed for persons born in Mexico. Adjusted models suggested that the spatial distribution of TB disease could not be fully explained using age, sex, country of birth and years since initial arrival. CONCLUSIONS: This study highlights areas of high TB incidence within Los Angeles County both for U.S.-born cases and for cases born in Mexico, Vietnam or the Philippines. It also highlights areas that had high incidence rates even when accounting for non-spatial error and country of birth, age, sex, and years since initial arrival in the U.S. Information on spatial distribution provided here complements other descriptions of local disease burden and may help focus ongoing efforts to scale up testing for TB infection and treatment among high-risk subgroups.

Challenges and solutions to estimating tuberculosis disease incidence by country of birth in Los Angeles County.

BACKGROUND: Among U.S. residents, tuberculosis (TB) disease disproportionally affects non-U.S.-born persons and varies substantially by country of birth. Yet TB disease incidence rates by country of birth are not routinely reported despite these large, known health disparities. This is in part due to the technical challenges of using standard regression analysis with a communicable disease. Here, we estimate tuberculosis disease incidence rates by country of birth and demonstrate methods for overcoming these challenges using TB surveillance data from Los Angeles County which has more than 3.5 million non-U.S.-born residents. METHODS: Cross-sectional data on 5,447 cases of TB disease from Los Angeles County were combined with population estimates from the American Community Survey to calculate TB disease incidence rates for 2005 through 2011. Adjusted incidence rates were modelled using Poisson and negative binomial regressions. Bayesian models were used to account for the uncertainty in population estimates. RESULTS: The unadjusted incidence rate among non-U.S.-born persons was 15 per 100,000 person-years in contrast to the rate among U.S-born persons, 2 per 100,000. The unadjusted incidence rates were 44 and 12 per 100,000 person-years among persons born in the Philippines and Mexico, respectively. In adjusted analysis, persons born in the Philippines were 2.6 (95% CI: 2.3-3.1) times as likely to be reported as a TB case than persons born in Mexico. Bayesian models showed similar results. CONCLUSION: This study confirms substantial disparities in TB disease by country of birth in Los Angeles County. Accounting for age, gender, years in residence and year of diagnosis, persons from the Philippines, Vietnam and several other countries had much higher rates of reported TB disease than other foreign countries. We demonstrated that incidence rates by country of birth can be estimated using available data despite technical challenges.

Multi-pollutant exposure profiles associated with term low birth weight in Los Angeles County.

Research indicates that multiple outdoor air pollutants and adverse neighborhood conditions are spatially correlated. Yet health risks associated with concurrent exposure to air pollution mixtures and clustered neighborhood factors remain underexplored. Statistical models to assess the health effects from pollutant mixtures remain limited, due to problems of collinearity between pollutants and area-level covariates, and increases in covariate dimensionality. Here we identify pollutant exposure profiles and neighborhood contextual profiles within Los Angeles (LA) County. We then relate these profiles with term low birth weight (TLBW). We used land use regression to estimate NO2, NO, and PM2.5 concentrations averaged over census block groups to generate pollutant exposure profile clusters and census block group-level contextual profile clusters, using a Bayesian profile regression method. Pollutant profile cluster risk estimation was implemented using a multilevel hierarchical model, adjusting for individual-level covariates, contextual profile cluster random effects, and modeling of spatially structured and unstructured residual error. Our analysis found 13 clusters of pollutant exposure profiles. Correlations between study pollutants varied widely across the 13 pollutant clusters. Pollutant clusters with elevated NO2, NO, and PM2.5 concentrations exhibited increased log odds of TLBW, and those with low PM2.5, NO2, and NO concentrations showed lower log odds of TLBW. The spatial patterning of pollutant cluster effects on TLBW, combined with between-pollutant correlations within pollutant clusters, imply that traffic-related primary pollutants influence pollutant cluster TLBW risks. Furthermore, contextual clusters with the greatest log odds of TLBW had more adverse neighborhood socioeconomic, demographic, and housing conditions. Our data indicate that, while the spatial patterning of high-risk multiple pollutant clusters largely overlaps with adverse contextual neighborhood cluster, both contribute to TLBW while controlling for the other.

Prenatal Maternal Stress and the Risk of Lifetime Wheeze in Young Offspring: An Examination by Stressor and Maternal Ethnicity.

Prenatal psychosocial stressors may increase the risk of wheeze in young offspring, yet little attention has been given to the effects that maternal ethnicity may have on this relationship. From a population-based cohort of 1193 children, we assessed the effect of maternal prenatal stressors on the risk of lifetime wheeze in young offspring. We further studied whether maternal Latina ethnicity modified these associations. The risk of wheeze in the offspring was increased from high levels of pregnancy anxiety (aRR 1.40, 95 % CI 1.07, 1.83), negative life events (aRR 1.36, 95 % CI 1.06, 1.75), or low paternal support (aRR 1.41, 95 % CI 1.02, 1.96). The risk of lifetime wheeze was stronger in the offspring of Latina mothers than of White mothers for these same stressors. Multiple maternal prenatal stressors are associated with increased risk of lifetime wheeze in young offspring, with slight effect modification by Latina ethnicity.

Prenatal exposure to traffic-related air pollution and risk of early childhood cancers.

Exposure to air pollution during pregnancy has been linked to the risk of childhood cancer, but the evidence remains inconclusive. In the present study, we used land use regression modeling to estimate prenatal exposures to traffic exhaust and evaluate the associations with cancer risk in very young children. Participants in the Air Pollution and Childhood Cancers Study who were 5 years of age or younger and diagnosed with cancer between 1988 and 2008 were had their records linked to California birth certificates, and controls were selected from birth certificates. Land use regression-based estimates of exposures to nitric oxide, nitrogen dioxide, and nitrogen oxides were assigned based on birthplace residence and temporally adjusted using routine monitoring station data to evaluate air pollution exposures during specific pregnancy periods. Logistic regression models were adjusted for maternal age, race/ethnicity, educational level, parity, insurance type, and Census-based socioeconomic status, as well as child's sex and birth year. The odds of acute lymphoblastic leukemia increased by 9%, 23%, and 8% for each 25-ppb increase in average nitric oxide, nitrogen dioxide, and nitrogen oxide levels, respectively, over the entire pregnancy. Second- and third-trimester exposures increased the odds of bilateral retinoblastoma. No associations were found for annual average exposures without temporal components or for any other cancer type. These results lend support to a link between prenatal exposure to traffic exhaust and the risk of acute lymphoblastic leukemia and bilateral retinoblastoma.

Estimating Spatiotemporal Variability of Ambient Air Pollutant Concentrations with A Hierarchical Model.

Studies have linked exposure to air pollutants to short-term and sub-chronic health outcomes. However, individual-level air pollution exposure is difficult to measure at a high spatial and temporal resolution and for larger populations due to limitations in sampling techniques. We presented a hierarchical model to capture spatiotemporal variability of nitrogen dioxide (NO2) and nitrogen oxides (NOx) concentrations in Southern California by combining high temporal resolution data from routine monitoring stations with high spatial resolution data from investigator-initiated episodic measurements. In this model, the spatiotemporal field of concentrations was first decomposed into a mean and residual and the mean representing the seasonal trend was further decomposed into a constant and varying temporal basis functions. The mean of the spatially varying coefficients of temporal basis functions were modeled by local covariates using non-linear generalized additive model and least square fitting using measurements from both routine monitoring and additional episodic sampling locations, while the spatially-correlated residuals of the coefficients were co-kriged. We found traffic, land-use and wind accounted for a large portion of the variance (beyond 35%) for the long-term average trend of concentrations. Spatial residuals accounted for a large portion of the variance of the temporal components (about 30% for NO2 and 20% for NOx). Leave-one-out cross validation produced an R2 of 0.84 for NO2 and 0.81 for NOx when comparing the modeled weekly concentration with the observed trends at all routine monitoring stations.

Effects of residential indoor air quality and household ventilation on preterm birth and term low birth weight in Los Angeles County, California.

OBJECTIVES: The purpose of our study was to examine the effects of indoor residential air quality on preterm birth and term low birth weight (LBW). METHODS: We evaluated 1761 nonsmoking women from a case-control survey of mothers who delivered a baby in 2003 in Los Angeles County, California. In multinomial logistic regression models adjusted for maternal age, education, race/ethnicity, parity and birthplace, we evaluated the effects of living with smokers or using personal or household products that may contain volatile organic compounds and examined the influence of household ventilation. RESULTS: Compared with unexposed mothers, women exposed to secondhand smoke (SHS) at home had increased odds of term LBW (adjusted odds ratio [OR] = 1.36; 95% confidence interval [CI] = 0.85, 2.18) and preterm birth (adjusted OR = 1.27; 95% CI = 0.95, 1.70), although 95% CIs included the null. No increase in risk was observed for SHS-exposed mothers reporting moderate or high window ventilation. Associations were also observed for product usage, but only for women reporting low or no window ventilation. CONCLUSIONS: Residential window ventilation may mitigate the effects of indoor air pollution among pregnant women in Los Angeles County, California.

Assessing the influence of traffic-related air pollution on risk of term low birth weight on the basis of land-use-based regression models and measures of air toxics.

Few studies have examined associations of birth outcomes with toxic air pollutants (air toxics) in traffic exhaust. This study included 8,181 term low birth weight (LBW) children and 370,922 term normal-weight children born between January 1, 1995, and December 31, 2006, to women residing within 5 miles (8 km) of an air toxics monitoring station in Los Angeles County, California. Additionally, land-use-based regression (LUR)-modeled estimates of levels of nitric oxide, nitrogen dioxide, and nitrogen oxides were used to assess the influence of small-area variations in traffic pollution. The authors examined associations with term LBW (≥37 weeks' completed gestation and birth weight <2,500 g) using logistic regression adjusted for maternal age, race/ethnicity, education, parity, infant gestational age, and gestational age squared. Odds of term LBW increased 2%-5% (95% confidence intervals ranged from 1.00 to 1.09) per interquartile-range increase in LUR-modeled estimates and monitoring-based air toxics exposure estimates in the entire pregnancy, the third trimester, and the last month of pregnancy. Models stratified by monitoring station (to investigate air toxics associations based solely on temporal variations) resulted in 2%-5% increased odds per interquartile-range increase in third-trimester benzene, toluene, ethyl benzene, and xylene exposures, with some confidence intervals containing the null value. This analysis highlights the importance of both spatial and temporal contributions to air pollution in epidemiologic birth outcome studies.

Traffic-related air toxics and term low birth weight in Los Angeles County, California.

BACKGROUND: Numerous studies have linked criteria air pollutants with adverse birth outcomes, but there is less information on the importance of specific emission sources, such as traffic, and air toxics. OBJECTIVES: We used three exposure data sources to examine odds of term low birth weight (LBW) in Los Angeles, California, women when exposed to high levels of traffic-related air pollutants during pregnancy. METHODS: We identified term births during 1 June 2004 to 30 March 2006 to women residing within 5 miles of a South Coast Air Quality Management District (SCAQMD) Multiple Air Toxics Exposure Study (MATES III) monitoring station. Pregnancy period average exposures were estimated for air toxics, including polycyclic aromatic hydrocarbons (PAHs), source-specific particulate matter < 2.5 µm in aerodynamic diameter (PM2.5) based on a chemical mass balance model, criteria air pollutants from government monitoring data, and land use regression (LUR) model estimates of nitric oxide (NO), nitrogen dioxide (NO2) and nitrogen oxides (NOx). Associations between these metrics and odds of term LBW (< 2,500 g) were examined using logistic regression. RESULTS: Odds of term LBW increased approximately 5% per interquartile range increase in entire pregnancy exposures to several correlated traffic pollutants: LUR measures of NO, NO2, and NOx, elemental carbon, and PM2.5 from diesel and gasoline combustion and paved road dust (geological PM2.5). CONCLUSIONS: These analyses provide additional evidence of the potential impact of traffic-related air pollution on fetal growth. Particles from traffic sources should be a focus of future studies.

Traffic-related air toxics and preterm birth: a population-based case-control study in Los Angeles County, California.

BACKGROUND: Numerous studies have associated air pollutant exposures with adverse birth outcomes, but there is still relatively little information to attribute effects to specific emission sources or air toxics. We used three exposure data sources to examine risks of preterm birth in Los Angeles women when exposed to high levels of traffic-related air pollutants--including specific toxics--during pregnancy. METHODS: We identified births during 6/1/04-3/31/06 to women residing within five miles of a Southern California Air Quality Management District (SCAQMD) Multiple Air Toxics Exposure Study (MATES III) monitoring station. We identified preterm cases and, using a risk set approach, matched cases to controls based on gestational age at birth. Pregnancy period exposure averages were estimated for a number of air toxics including polycyclic aromatic hydrocarbons (PAHs), source-specific PM2.5 (fine particulates with aerodynamic diameter less than 2.5 µm) based on a Chemical Mass Balance model, criteria air pollutants based on government monitoring data, and land use regression (LUR) estimates of nitric oxide (NO), nitrogen dioxide (NO2) and nitrogen oxides (NOx). Associations between these metrics and odds of preterm birth were estimated using conditional logistic regression. RESULTS: Odds of preterm birth increased 6-21% per inter-quartile range increase in entire pregnancy exposures to organic carbon (OC), elemental carbon (EC), benzene, and diesel, biomass burning and ammonium nitrate PM2.5, and 30% per inter-quartile increase in PAHs; these pollutants were positively correlated and clustered together in a factor analysis. Associations with LUR exposure metrics were weaker (3-4% per inter-quartile range increase). CONCLUSIONS: These latest analyses provide additional evidence of traffic-related air pollution's impact on preterm birth for women living in Southern California and indicate PAHs as a pollutant of concern that should be a focus of future studies. Other PAH sources besides traffic were also associated with higher odds of preterm birth, as was ammonium nitrate PM2.5, the latter suggesting potential importance of secondary pollutants. Future studies should focus on accurate modeling of both local and regional spatial and temporal distributions, and incorporation of source information.

Paternal support and preterm birth, and the moderation of effects of chronic stress: a study in Los Angeles county mothers.

Maternal psychosocial stress is an important risk factor for preterm birth, but support interventions have largely been unsuccessful. The objective of this study is to assess how support during pregnancy influences preterm birth risk and possibly ameliorates the effects of chronic stress, life event stress, or pregnancy anxiety in pregnant women. We examined 1,027 singleton preterm births and 1,282 full-term normal weight controls from a population-based retrospective case-control study of Los Angeles County, California women giving birth in 2003, a mostly Latina population (both US-born and immigrant). We used logistic regression to assess whether support from the baby's father during pregnancy influences birth outcomes and effects of chronic stress, pregnancy anxiety, and life event stress. Adjusted odds of preterm birth decreased with better support (OR 0.73 [95%CI 0.52, 1.01]). Chronic stress (OR 1.46 [95%CI 1.11, 1.92]), low confidence of a normal birth (OR 1.57 [95% CI 1.17, 2.12]), and fearing for the baby's health (OR 1.67 [95%CI 1.30, 2.14]) increased preterm birth risk, but life events showed no association. Our data also suggested that paternal support may modify the effect of chronic stress on the risk of preterm birth, such that among mothers lacking support, those with moderate-to-high stress were at increased odds of delivering preterm (OR 2.15 [95%CI 0.92, 5.03]), but women with greater support had no increased risk with moderate-to-high chronic stress (OR 1.13 [95%CI 0.94, 1.35]). Paternal support may moderate the effects of chronic stress on the risk of preterm delivery.

Predicting traffic-related air pollution in Los Angeles using a distance decay regression selection strategy.

Land use regression (LUR) has emerged as an effective means of estimating exposure to air pollution in epidemiological studies. We created the first LUR models of nitric oxide (NO), nitrogen dioxide (NO2) and nitrogen oxides (NOX) for the complex megalopolis of Los Angeles (LA), California. Two-hundred and one sampling sites (the largest sampling design to date for LUR estimation) for two seasons were selected using a location-allocation algorithm that maximized the potential variability in measured pollutant concentrations and represented populations in the health study. Traffic volumes, truck routes and road networks, land use data, satellite-derived vegetation greenness and soil brightness, and truck route slope gradients were used for predicting NOX concentrations. A novel model selection strategy known as "ADDRESS" (A Distance Decay REgression Selection Strategy) was used to select optimized buffer distances for potential predictor variables and maximize model performance. Final regression models explained 81%, 86% and 85% of the variance in measured NO, NO2 and NOX concentrations, respectively. Cross-validation analyses suggested a prediction accuracy of 87-91%. Remote sensing-derived variables were significantly correlated with NOX concentrations, suggesting these data are useful surrogates for modeling traffic-related pollution when certain land use data are unavailable. Our study also demonstrated that reactive pollutants such as NO and NO2 could have high spatial extents of influence (e.g., > 5000 m from expressway) and high background concentrations in certain geographic areas. This paper represents the first attempt to model traffic-related air pollutants at a fine scale within such a complex and large urban region.

Ambient air pollution and preterm birth in the environment and pregnancy outcomes study at the University of California, Los Angeles.

The authors conducted a case-control survey nested within a birth cohort and collected detailed risk factor information to assess the extent to which residual confounding and exposure misclassification may impact air pollution effect estimates. Using a survey of 2,543 of 6,374 women sampled from a cohort of 58,316 eligible births in 2003 in Los Angeles County, California, the authors estimated with logistic regression and two-phase models the effects of pregnancy period-specific air pollution exposure on the odds of preterm birth. For the first trimester, the odds of preterm birth consistently increased with increasing carbon monoxide exposures and also at high levels of exposure to particulate matter less than or equal to 2.5 microm in diameter (>21.4 microg/m(3)), regardless of type of data (cohort/sample) or covariate adjustment (carbon monoxide exposures of >1.25 ppm increased the odds by 21-25%). Women exposed to carbon monoxide above 0.91 ppm during the last 6 weeks of pregnancy experienced increased odds of preterm birth. Crude and birth certificate covariate-adjusted results for carbon monoxide differed from each other. However, further adjustment for risk factors assessed in the survey did not change effect estimates for short-term pollutant averages appreciably, except for time-activity patterns, which strengthened the observed associations. These results confirm the importance of reducing exposure misclassification when evaluating the effect of traffic-related pollutants that vary spatially.