Near-roadway air pollution associated with COVID-19 severity and mortality - Multiethnic cohort study in Southern California

Causal relationship between particulate matter and COVID-19 risk: A mendelian randomization study

Background

Observational studies have linked exposure to fine (PM2.5) and coarse (PM10) particulate matter air pollution with adverse COVID-19 outcomes, including higher incidence and mortality. However, some studies questioned the effect of air pollution on COVID-19 susceptibility, raising questions about the causal nature of these associations. To address this, a less biased method like Mendelian randomization (MR) is utilized, which employs genetic variants as instrumental variables to infer causal relationships in observational data.

Method

We performed two-sample MR analysis using public genome-wide association studies data. Instrumental variables correlated with PM2.5 concentration, PM2.5 absorbance, PM2.5-10 concentration and PM10 concentration were identified. The inverse variance weighted (IVW), robust adjusted profile score (RAPS) and generalized summary data-based Mendelian randomization (GSMR) methods were used for analysis.

Results

IVW MR analysis showed PM2.5 concentration [odd ratio (OR) = 3.29, 95% confidence interval (CI) 1.48-7.35, P-value = 0.0036], PM2.5 absorbance (OR = 5.62, 95%CI 1.98-15.94, P-value = 0.0012), and PM10 concentration (OR = 3.74, 95%CI 1.52-9.20, P-value = 0.0041) increased the risk of COVID-19 severity after Bonferroni correction. Further validation confirmed PM2.5 absorbance was associated with heightened COVID-19 severity (OR = 6.05, 95%CI 1.99-18.38, P-value = 0.0015 for RAPS method; OR = 4.91, 95%CI 1.65-14.59, P-value = 0.0042 for GSMR method) and hospitalization (OR = 3.15, 95%CI 1.54-6.47, P-value = 0.0018 for RAPS method). No causal links were observed between particulate matter exposure and COVID-19 susceptibility.

Conclusions

Our study established a causal relationship between smaller particle pollution, specifically PM2.5, and increased risk of COVID-19 severity and hospitalization. These findings highlight the importance of improving air quality to mitigate respiratory disease progression.

The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis

BACKGROUND

The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims to synthesize findings from ecological and non-ecological studies to investigate the impact of multiple urban-related features on a variety of COVID-19 health outcomes.

METHODS

On December 5, 2022, PubMed was searched to identify all types of observational studies that examined one or more urban exposome characteristics in relation to various COVID-19 health outcomes such as infection severity, the need for hospitalization, ICU admission, COVID pneumonia, and mortality.

RESULTS

A total of 38 non-ecological and 241 ecological studies were included in this review. Non-ecological studies highlighted the significant effects of population density, urbanization, and exposure to ambient air pollutants, particularly PM2.5. The meta-analyses revealed that a 1 μg/m3 increase in PM2.5 was associated with a higher likelihood of COVID-19 hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) and death (pooled OR 1.06 (95% CI:1.03-1.09)). Ecological studies, in addition to confirming the findings of non-ecological studies, also indicated that higher exposure to nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), and carbon monoxide (CO), as well as lower ambient temperature, humidity, ultraviolet (UV) radiation, and less green and blue space exposure, were associated with increased COVID-19 morbidity and mortality.

CONCLUSION

This systematic review has identified several key vulnerability features related to urban areas in the context of the recent COVID-19 pandemic. The findings underscore the importance of improving policies related to urban exposures and implementing measures to protect individuals from these harmful environmental stressors.

Air pollution and the sequelae of COVID-19 patients: A multistate analysis

IMPORTANCE

Recent evidence links air pollution to the severity COVID-19 symptoms and to death from the disease. To date, however, few studies have assessed whether air pollution affects the sequelae to more severe states or recovery from COVID-19 in a cohort with individual data.

OBJECTIVE

To assess how air pollution affects the transition to more severe COVID-19 states or to recovery from COVID-19 infection in a cohort with detailed patient information.

DESIGN AND OUTCOMES

We used a cohort design that followed patients admitted to hospital in the Kaiser Permanente Southern California (KPSC) Health System, which has 4.7 million members with characteristics similar to the general population. Enrollment began on 06/01/2020 and ran until 01/30/2021 for all patients admitted to hospital while ill with COVID-19. All possible states of sequelae were considered, including deterioration to intensive care, to death, discharge to recovery, or discharge to death. Transition risks were estimated with a multistate model. We assessed exposure using chemical transport model that predicted ambient concentrations of nitrogen dioxide, ozone, and fine particulate matter (PM2.5) at a 1 km scale.

RESULTS

Each increase in PM2.5 concentration equivalent to the interquartile range was associated with increased risk of deterioration to intensive care (HR of 1.16; 95% CI: 1.12-1.20) and deterioration to death (HR of 1.11; 95% CI: 1.04-1.17). Results for ozone were consistent with PM2.5 effects, but ozone also affected the transition from recovery to death: HR of 1.24 (95% CI: 1.01-1.51). NO2 had weaker effects but displayed some elevated risks.

CONCLUSIONS

PM2.5 and ozone were significantly associated with transitions to more severe states while in hospital and to death after discharge from hospital. Reducing air pollution could therefore lead to improved prognosis for COVID-19 patients and a sustainable means of reducing the health impacts of coronaviruses now and in the future.

NYS Nonprofit Hospital Assessment and Response to Environmental Pollution as Community Health Need: Prevalence in Community Benefit Practices

CONTEXT

Given the impact of environmental pollution on health and health inequity, there may be substantial value in integrating assessment and response to pollution into nonprofit hospital community benefit processes. Such hospital engagement has not yet been studied.

OBJECTIVES

We take a preliminary step of inquiry in investigating if nonprofit hospitals in New York State (NYS) assess, identify, or respond to environmental pollution as part of community benefit processes.

DESIGN

This study is of retrospective, observational design. Data were abstracted from community health needs reports (2015-2017), associated implementation plans, and related IRS (Internal Revenue Service) filings from a randomly geographically stratified selection of NYS nonprofit hospitals.

PARTICIPANTS

The sample includes 53 hospitals from 23 counties. The sampling frame consists of NYS nonspecialty private nonprofit hospitals.

MAIN OUTCOME MEASURES

Dichotomous findings for the following: (1) engagement of environmental pollution in the process of assessment of community health needs; (2) environmental pollution concern identified as a priority community health need; (3) strategic planning present to address pollution identified as community health need; and (4) action taken on same.

RESULTS

We found that 60.5% (95% confidence interval [CI], 0.46-0.74) of hospitals evidenced some form of assessment of environmental pollution and 18.9% (95% CI, 0.09-0.32) identified pollution as a priority community health need. However, no hospital went on to take independent or collaborative planning or action to address pollution. In additional analysis, we found that social justice in hospital mission was a positive predictor of assessment of environmental pollution.

CONCLUSIONS

For NYS hospitals, we found a substantial presence of assessment and identification of pollution as a community health concern. Our finding of the absence of response to environmental pollution represents a gap in community benefit implementation. This indicates a yet untaken opportunity to address racial and economic environmental health injustices and to improve population health.

Combining aggregate and individual-level data to estimate individual-level associations between air pollution and COVID-19 mortality in the United States

Imposing stricter regulations for PM2.5 has the potential to mitigate damaging health and climate change effects. Recent evidence establishing a link between exposure to air pollution and COVID-19 outcomes is one of many arguments for the need to reduce the National Ambient Air Quality Standards (NAAQS) for PM2.5. However, many studies reporting a relationship between COVID-19 outcomes and PM2.5 have been criticized because they are based on ecological regression analyses, where area-level counts of COVID-19 outcomes are regressed on area-level exposure to air pollution and other covariates. It is well known that regression models solely based on area-level data are subject to ecological bias, i.e., they may provide a biased estimate of the association at the individual-level, due to within-area variability of the data. In this paper, we augment county-level COVID-19 mortality data with a nationally representative sample of individual-level covariate information from the American Community Survey along with high-resolution estimates of PM2.5 concentrations obtained from a validated model and aggregated to the census tract for the contiguous United States. We apply a Bayesian hierarchical modeling approach to combine county-, census tract-, and individual-level data to ultimately draw inference about individual-level associations between long-term exposure to PM2.5 and mortality for COVID-19. By analyzing data prior to the Emergency Use Authorization for the COVID-19 vaccines we found that an increase of 1 μg/m3 in long-term PM2.5 exposure, averaged over the 17-year period 2000-2016, is associated with a 3.3% (95% credible interval, 2.8 to 3.8%) increase in an individual's odds of COVID-19 mortality. Code to reproduce our study is publicly available at https://github.com/NSAPH/PM_COVID_ecoinference. The results confirm previous evidence of an association between long-term exposure to PM2.5 and COVID-19 mortality and strengthen the case for tighter regulations on harmful air pollution and greenhouse gas emissions.

Pre-admission ambient air pollution and blood soot particles predict hospitalisation outcomes in COVID-19 patients

BACKGROUND

Air pollution exposure is one of the major risk factors for aggravation of respiratory diseases. We investigated whether exposure to air pollution and accumulated black carbon (BC) particles in blood were associated with coronavirus disease 2019 (COVID-19) disease severity, including the risk for intensive care unit (ICU) admission and duration of hospitalisation.

METHODS

From May 2020 until March 2021, 328 hospitalised COVID-19 patients (29% at intensive care) were recruited from two hospitals in Belgium. Daily exposure levels (from 2016 to 2019) for particulate matter with aerodynamic diameter <2.5 µm and <10 µm (PM2.5 and PM10, respectively), nitrogen dioxide (NO2) and BC were modelled using a high-resolution spatiotemporal model. Blood BC particles (internal exposure to nano-sized particles) were quantified using pulsed laser illumination. Primary clinical parameters and outcomes included duration of hospitalisation and risk of ICU admission.

RESULTS

Independent of potential confounders, an interquartile range (IQR) increase in exposure in the week before admission was associated with increased duration of hospitalisation (PM2.5 +4.13 (95% CI 0.74-7.53) days, PM10 +4.04 (95% CI 1.24-6.83) days and NO2 +4.54 (95% CI 1.53-7.54) days); similar effects were observed for long-term NO2 and BC exposure on hospitalisation duration. These effect sizes for an IQR increase in air pollution on hospitalisation duration were equivalent to the effect of a 10-year increase in age on hospitalisation duration. Furthermore, for an IQR higher blood BC load, the OR for ICU admission was 1.33 (95% CI 1.07-1.65).

CONCLUSIONS

In hospitalised COVID-19 patients, higher pre-admission ambient air pollution and blood BC levels predicted adverse outcomes. Our findings imply that air pollution exposure influences COVID-19 severity and therefore the burden on medical care systems during the COVID-19 pandemic.

Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors

The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.

Air pollution and meteorology as risk factors for COVID-19 death in a cohort from Southern California

BACKGROUND

Recent evidence links ambient air pollution to COVID-19 incidence, severity, and death, but few studies have analyzed individual-level mortality data with high quality exposure models.

METHODS

We sought to assess whether higher air pollution exposures led to greater risk of death during or after hospitalization in confirmed COVID-19 cases among patients who were members of the Kaiser Permanente Southern California (KPSC) healthcare system (N=21,415 between 06-01-2020 and 01-31-2022 of whom 99.85 % were unvaccinated during the study period). We used 1 km resolution chemical transport models to estimate ambient concentrations of several common air pollutants, including ozone, nitrogen dioxide, and fine particle matter (PM_2.5). We also derived estimates of pollutant exposures from ultra-fine particulate matter (PM_0.1), PM chemical species, and PM sources. We employed Cox proportional hazards models to assess associations between air pollution exposures and death from COVID-19 among hospitalized patients.

FINDINGS

We found significant associations between COVID-19 death and several air pollution exposures, including: PM_2.5 mass, PM_0.1 mass, PM_2.5 nitrates, PM_2.5 elemental carbon, PM_2.5 on-road diesel, and PM_2.5 on-road gasoline. Based on the interquartile (IQR) exposure increment, effect sizes ranged from hazard ratios (HR) = 1.12 for PM_2.5 mass and PM_2.5 nitrate to HR ∼ 1.06-1.07 for other species or source markers. Humidity and temperature in the month of diagnosis were also significant negative predictors of COVID-19 death and negative modifiers of the air pollution effects.

INTERPRETATION

Air pollution exposures and meteorology were associated the risk of COVID-19 death in a cohort of patients from Southern California. These findings have implications for prevention of death from COVID-19 and for future pandemics.

Climate Crises and Developing Vector-Borne Diseases: A Narrative Review

Background

Climate change based on temperature, humidity and wind can improve many characteristics of the arthropod carrier life cycle, including survival, arthropod population, pathogen communication, and the spread of infectious agents from vectors. This study aimed to find association between content of disease followed climate change we demonstrate in humans.

Methods

All the articles from 2016 to 2021 associated with global climate change and the effect of vector-borne disease were selected form databases including PubMed and the Global Biodiversity information facility database. All the articles selected for this short review were English.

Results

Due to the high burden of infectious diseases and the growing evidence of the possible effects of climate change on the incidence of these diseases, these climate changes can potentially be involved with the COVID-19 epidemic. We highlighted the evidence of vector-borne diseases and the possible effects of climate change on these communicable diseases.

Conclusion

Climate change, specifically in rising temperature system is one of the world's greatest concerns already affected pathogen-vector and host relation. Lice parasitic, fleas, mites, ticks, and mosquitos are the prime public health importance in the transmission of virus to human hosts.

The correlation between attack rates and urban health indicators during the third wave of the COVID-19 outbreak in Turkey

This study aims to analyze the inter-provincial variation in the increase of attack rates in the third wave of the COVID-19 outbreak in Turkey and to determine their relationship with potential urban health indicators. In this ecological study, dependent variables were selected as the COVID-19 attack rates of provinces before the third wave and during the third peak and the attack rate increase ratio. Urban health indicators that can function as determinants of health were calculated for each province under five headings: demographic, health capacity, economic, environmental, and socio-cultural. The epidemiologic maps were produced to show the spatial distribution of COVID-19 attack rates pre- and during the third wave. The associations with urban indicators were conducted using bivariate analysis, including Pearson or Spearman correlation analysis. A multiple linear regression model was run with variables significantly associated with increased attack rates. The results of our study show significant regional variations in COVID-19 attack rates both at the beginning and during the third wave of the COVID-19 pandemic in Turkey. Among the provinces, the attack rate increase ratio has only shown significant correlations to education level and some economic indicators, such as income, employment, industrial activity measured by electric consumption, and economic activity in the manufacturing industry. The multivariate analysis determined that the indicator of economic activity in the manufacturing industry is related to the increase of the attack rate in the third wave. Our results show that the COVID-19 cases are higher in more developed cities with more manufacturing sector activity. It makes us think that it is mainly related to inequalities arising from access to health institutions and testing. It can be determined that the partly lockdown strategy, which excluded the industrial activity in the country, concluded the higher increase in the attack rates in highly industrialized provinces.

Association between Short-Term Exposure to Air Pollution and COVID-19 Mortality: A Population-Based Case-Crossover Study Using Individual-Level Mortality Registry Confirmed by Medical Examiners

BACKGROUND

Studies have suggested links between ambient air pollution and coronavirus 2019 (COVID-19) mortality, yet confirmation by well-designed epidemiological studies with individual data is needed.

OBJECTIVES

We aimed to examine whether short-term exposure to air pollution is associated with risk of mortality from COVID-19 for those infected with COVID-19.

METHODS

The Cook County Medical Examiner's Office reports individual-level data for deaths from COVID-19 that occur in its jurisdiction, which includes all confirmed COVID-19 deaths in Cook County, Illinois. Case-crossover analysis was conducted to estimate the associations of estimated short-term exposures to particulate matter (PM) with aerodynamic diameter ≤2.5μm (PM2.5) and ozone (O3) on the day of death and up to 21 d before death at location of death with COVID-19. A total of 7,462 deaths from COVID-19 that occurred up to 28 February 2021 were included in the final analysis. We adjusted for potential confounders by time-stratified case-crossover design and by covariate adjustments (i.e., time-invariant factors, meteorological factors, viral transmission, seasonality, and time trend).

RESULTS

Of the 7,462 case and 25,457 self-control days, almost all were days with exposure levels below the PM2.5 24-h National Ambient Air Quality Standard (NAAQS) (35 μg/m3); 98.9% had O3 levels below the maximum 8-h NAAQS (35.7 μg/m3 or 70 parts per billion). An interquartile range (IQR) increase (5.2 μg/m3) in cumulative 3-wk PM2.5 exposure was associated with a 69.6% [95% confidence interval (CI): 34.6, 113.8] increase in risk of COVID-19 mortality. An IQR increase (8.2 μg/m3) in 3-d O3 exposure was associated with a 29.0% (95% CI: 9.9, 51.5) increase in risk of COVID-19 mortality. The associations differed by demographics or race/ethnicity. There was indication of modification of the associations by some comorbid conditions.

DISCUSSION

Short-term exposure to air pollution below the NAAQS may increase the mortality burden from COVID-19. https://doi.org/10.1289/EHP10836.

Association between long-term exposure to particulate air pollution with SARS-CoV-2 infections and COVID-19 deaths in California, U.S.A

Previous studies have reported associations between air pollution and COVID-19 morbidity and mortality, but most have limited their exposure assessment to a large area, have not used individual-level variables, nor studied infections. We examined 3.1 million SARS-CoV-2 infections and 49,691 COVID-19 deaths that occurred in California from February 2020 to February 2021 to evaluate risks associated with long-term neighborhood concentrations of particulate matter less than 2.5 μm in diameter (PM2.5). We obtained individual address data on SARS-CoV-2 infections and COVID-19 deaths and assigned 2000-2018 1km-1km gridded PM2.5 surfaces to census block groups. We included individual covariate data on age and sex, and census block data on race/ethnicity, air basin, Area Deprivation Index, and relevant comorbidities. Our analyses were based on generalized linear mixed models utilizing a Poisson distribution. Those living in the highest quintile of long-term PM2.5 exposure had risks of SARS-CoV-2 infections 20% higher and risks of COVID-19 mortality 51% higher, compared to those living in the lowest quintile of long-term PM2.5 exposure. Those living in the areas of highest long-term PM2.5 exposure were more likely to be Hispanic and more vulnerable, based on the Area Deprivation Index. The increased risks for SARS-CoV-2 Infections and COVID-19 mortality associated with highest long-term PM2.5 concentrations at the neighborhood-level in California were consistent with a growing body of literature from studies worldwide, and further highlight the importance of reducing levels of air pollution to protect public health.

Factors Modulating COVID-19: A Mechanistic Understanding Based on the Adverse Outcome Pathway Framework

Addressing factors modulating COVID-19 is crucial since abundant clinical evidence shows that outcomes are markedly heterogeneous between patients. This requires identifying the factors and understanding how they mechanistically influence COVID-19. Here, we describe how eleven selected factors (age, sex, genetic factors, lipid disorders, heart failure, gut dysbiosis, diet, vitamin D deficiency, air pollution and exposure to chemicals) influence COVID-19 by applying the Adverse Outcome Pathway (AOP), which is well-established in regulatory toxicology. This framework aims to model the sequence of events leading to an adverse health outcome. Several linear AOPs depicting pathways from the binding of the virus to ACE2 up to clinical outcomes observed in COVID-19 have been developed and integrated into a network offering a unique overview of the mechanisms underlying the disease. As SARS-CoV-2 infectibility and ACE2 activity are the major starting points and inflammatory response is central in the development of COVID-19, we evaluated how those eleven intrinsic and extrinsic factors modulate those processes impacting clinical outcomes. Applying this AOP-aligned approach enables the identification of current knowledge gaps orientating for further research and allows to propose biomarkers to identify of high-risk patients. This approach also facilitates expertise synergy from different disciplines to address public health issues.

Pollution and health: a progress update

The Lancet Commission on pollution and health reported that pollution was responsible for 9 million premature deaths in 2015, making it the world's largest environmental risk factor for disease and premature death. We have now updated this estimate using data from the Global Burden of Diseases, Injuriaes, and Risk Factors Study 2019. We find that pollution remains responsible for approximately 9 million deaths per year, corresponding to one in six deaths worldwide. Reductions have occurred in the number of deaths attributable to the types of pollution associated with extreme poverty. However, these reductions in deaths from household air pollution and water pollution are offset by increased deaths attributable to ambient air pollution and toxic chemical pollution (ie, lead). Deaths from these modern pollution risk factors, which are the unintended consequence of industrialisation and urbanisation, have risen by 7% since 2015 and by over 66% since 2000. Despite ongoing efforts by UN agencies, committed groups, committed individuals, and some national governments (mostly in high-income countries), little real progress against pollution can be identified overall, particularly in the low-income and middle-income countries, where pollution is most severe. Urgent attention is needed to control pollution and prevent pollution-related disease, with an emphasis on air pollution and lead poisoning, and a stronger focus on hazardous chemical pollution. Pollution, climate change, and biodiversity loss are closely linked. Successful control of these conjoined threats requires a globally supported, formal science-policy interface to inform intervention, influence research, and guide funding. Pollution has typically been viewed as a local issue to be addressed through subnational and national regulation or, occasionally, using regional policy in higher-income countries. Now, however, it is increasingly clear that pollution is a planetary threat, and that its drivers, its dispersion, and its effects on health transcend local boundaries and demand a global response. Global action on all major modern pollutants is needed. Global efforts can synergise with other global environmental policy programmes, especially as a large-scale, rapid transition away from all fossil fuels to clean, renewable energy is an effective strategy for preventing pollution while also slowing down climate change, and thus achieves a double benefit for planetary health.

Environmental Factors Influencing COVID-19 Incidence and Severity

Emerging evidence supports a link between environmental factors-including air pollution and chemical exposures, climate, and the built environment-and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and coronavirus disease 2019 (COVID-19) susceptibility and severity. Climate, air pollution, and the built environment have long been recognized to influence viral respiratory infections, and studies have established similar associations with COVID-19 outcomes. More limited evidence links chemical exposures to COVID-19. Environmental factors were found to influence COVID-19 through four major interlinking mechanisms: increased risk of preexisting conditions associated with disease severity; immune system impairment; viral survival and transport; and behaviors that increase viral exposure. Both data and methodologic issues complicate the investigation of these relationships, including reliance on coarse COVID-19 surveillance data; gaps in mechanistic studies; and the predominance of ecological designs. We evaluate the strength of evidence for environment-COVID-19 relationships and discuss environmental actions that might simultaneously address the COVID-19 pandemic, environmental determinants of health, and health disparities.

The effects of air pollution, meteorological parameters, and climate change on COVID-19 comorbidity and health disparities: A systematic review

Air pollutants, especially particulate matter, and other meteorological factors serve as important carriers of infectious microbes and play a critical role in the spread of disease. However, there remains uncertainty about the relationship among particulate matter, other air pollutants, meteorological conditions and climate change and the spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), hereafter referred to as COVID-19. A systematic review was conducted using PRISMA guidelines to identify the relationship between air quality, meteorological conditions and climate change, and COVID-19 risk and outcomes, host related factors, co-morbidities and disparities. Out of a total of 170,296 scientific publications screened, 63 studies were identified that focused on the relationship between air pollutants and COVID-19. Additionally, the contribution of host related-factors, co-morbidities, and health disparities was discussed. This review found a preponderance of evidence of a positive relationship between PM_2.5, other air pollutants, and meteorological conditions and climate change on COVID-19 risk and outcomes. The effects of PM_2.5, air pollutants, and meteorological conditions on COVID-19 mortalities were most commonly experienced by socially disadvantaged and vulnerable populations. Results however, were not entirely consistent, and varied by geographic region and study. Opportunities for using data to guide local response to COVID-19 are identified.