COVID-19 Case Surveillance: Trends in Person-Level Case Data Completeness, United States, April 5-September 30, 2020

Mortality Surveillance for the COVID-19 Pandemic: Review of the Centers for Disease Control and Prevention's Multiple System Strategy

Mortality surveillance systems can have limitations, including reporting delays, incomplete reporting, missing data, and insufficient detail on important risk or sociodemographic factors that can impact the accuracy of estimates of current trends, disease severity, and related disparities across subpopulations. The Centers for Disease Control and Prevention used multiple data systems during the COVID-19 emergency response-line-level case‒death surveillance, aggregate death surveillance, and the National Vital Statistics System-to collectively provide more comprehensive and timely information on COVID-19‒associated mortality necessary for informed decisions. This article will review in detail the line-level, aggregate, and National Vital Statistics System surveillance systems and the purpose and use of each. This retrospective review of the hybrid surveillance systems strategy may serve as an example for adaptive informational approaches needed over the course of future public health emergencies. (Am J Public Health. 2024;114(10):1071-1080. https://doi.org/10.2105/AJPH.2024.307743).

Data Equity as a Building Block for Health Equity: Improving Surveillance Data for People With Disabilities, With Substance Use Disorder, or Experiencing Homelessness, United States

OBJECTIVES

People with disabilities, people experiencing homelessness, and people who have substance use disorders face unique health challenges. Gaps in public health surveillance data limit the identification of public health needs of these groups and data-driven action. This study aimed to identify current practices, challenges, and opportunities for collecting and reporting COVID-19 surveillance data for these populations.

METHODS

We used a rapid qualitative assessment to explore COVID-19 surveillance capacities. From July through October 2021, we virtually interviewed key informants from the Centers for Disease Control and Prevention, state and local health departments, and health care providers across the United States. We thematically analyzed and contextualized interview notes, peer-reviewed articles, and participant documents using a literature review.

RESULTS

We identified themes centered on foundational structural and systems issues that hinder actionable surveillance data for these and other populations that are disproportionately affected by multiple health conditions. Qualitative data analysis of 61 interviews elucidated 4 primary challenges: definitions and policies, resources, data systems, and articulation of the purpose of data collection to these groups. Participants noted the use of multisector partnerships, automated data collection and integration, and data scorecards to circumvent challenges.

CONCLUSIONS

This study highlights the need for multisector, systematic improvements in surveillance data collection and reporting to advance health equity. Improvements must be buttressed with adequate investment in data infrastructure and promoted through clear communication of how data are used to protect health.

Measles epidemiological surveillance system before and during the COVID-19 pandemic in Pernambuco, Brazil, 2018-2022: a descriptive evaluation

OBJECTIVE

To evaluate the measles epidemiological surveillance system, before and during the COVID-19 pandemic in Pernambuco, Brazil.

METHODS

This was a descriptive evaluation of the quality (duplicity; completeness; consistency), timeliness and usefulness attributed, classified as excellent ≥ 90.0%, regular ≥ 70.0% and < 90.0%, and poor (< 70.0%). Data from the Notifiable Health Conditions Information System and Laboratory Environment Management System were used, before (03/11/2018-03/10/2020) and during (03/11/2020-03/10/2022) the pandemic.

RESULTS

1,548 suspected measles cases were registered (1,469 before and 79 during the pandemic). In the two periods studied, there were 11 and 1 duplicate records, average completeness in filling out the variables was 99.2% and 95.7%, while average consistency was 96.7% and 97.5%, respectively. Timeliness (receipt of samples, 16.2% and 33.0%. Release of results, 1.3% and 1.3%) and usefulness (43.5% and 24.4%) were poor.

CONCLUSION

Quality was classified as excellent in the periods studied, timeliness and usefulness were classified as poor, signaling non-compliance with the purpose of the system.

MAIN RESULTS

The quality of data from the measles epidemiological surveillance system in Pernambuco was excellent, while its timeliness and usefulness were poor during both periods.

IMPLICATIONS FOR SERVICES

The limited timeliness and, therefore, the low usefulness of the measles epidemiological surveillance system must be discussed in the three government spheres of health service management, with the aim of training the professionals involved, as well as monitoring and evaluating the system.

PERSPECTIVES

Systematic monitoring and evaluation generates evidence that supports health service managers and workers in the timely identification of gaps that compromise the full fulfillment of the objectives proposed.

Completeness of Race and Ethnicity Reporting in Person-Level COVID-19 Surveillance Data, 50 States, April 2020-December 2021

OBJECTIVES

Black, Indigenous, and People of Color have borne a disproportionate incidence of COVID-19 cases in the United States. However, few studies have documented the completeness of race and ethnicity reporting in national COVID-19 surveillance data. The objective of this study was to describe the completeness of race and ethnicity ascertainment in person-level data received by the Centers for Disease Control and Prevention (CDC) through national COVID-19 case surveillance.

METHODS

We compared COVID-19 cases with "complete" (ie, per Office of Management and Budget 1997 revised criteria) data on race and ethnicity from CDC person-level surveillance data with CDC-reported aggregate counts of COVID-19 from April 5, 2020, through December 1, 2021, in aggregate and by state.

RESULTS

National person-level COVID-19 case surveillance data received by CDC during the study period included 18 881 379 COVID-19 cases with complete ascertainment of race and ethnicity, representing 39.4% of all cases reported to CDC in aggregate (N = 47 898 497). Five states (Georgia, Hawaii, Nebraska, New Jersey, and West Virginia) did not report any COVID-19 person-level cases with multiple racial identities to CDC.

CONCLUSION

Our findings highlight a high degree of missing data on race and ethnicity in national COVID-19 case surveillance, enhancing our understanding of current challenges in using these data to understand the impact of COVID-19 on Black, Indigenous, and People of Color. Streamlining surveillance processes to decrease reporting incidence and align reporting requirements with an Office of Management and Budget-compliant collection of data on race and ethnicity would improve the completeness of data on race and ethnicity for national COVID-19 case surveillance.

COVID-19 on the Nile: a cross-sectional investigation of COVID-19 among Nile River cruise travellers returning to the United States, February-March 2020

BACKGROUND

Early in the pandemic, cruise travel exacerbated the global spread of SARS-CoV-2. We report epidemiologic and molecular findings from an investigation of a cluster of travellers with confirmed COVID-19 returning to the USA from Nile River cruises in Egypt.

METHODS

State health departments reported data on real-time reverse transcription-polymerase chain reaction-confirmed COVID-19 cases with a history of Nile River cruise travel during February-March 2020 to the Centers for Disease Control and Prevention (CDC). Demographic and epidemiologic data were collected through routine surveillance channels. Sequences were obtained either from state health departments or from the Global Initiative on Sharing Avian Flu Data (GISAID). We conducted descriptive analyses of epidemiologic data and explored phylogenetic relationships between sequences.

RESULTS

We identified 149 Nile River cruise travellers with confirmed COVID-19 who returned to 67 different US counties in 27 states: among those with complete data, 4.7% (6/128) died and 28.1% (38/135) were hospitalized. These individuals travelled on 20 different Nile River cruise voyages (12 unique vessels). Fifteen community transmission events were identified in four states, with 73.3% (11/15) of these occurring in Wisconsin (as the result of a more detailed contact investigation in that state). Phylogenetic analyses supported the hypothesis that travellers were most likely infected in Egypt, with most sequences in Nextstrain clade 20A 93% (87/94). We observed genetic clustering by Nile River cruise voyage and vessel.

CONCLUSIONS

Nile River cruise travellers with COVID-19 introduced SARS-CoV-2 over a very large geographic range, facilitating transmission across the USA early in the pandemic. Travellers who participate in cruises, even on small river vessels as investigated in this study, are at increased risk of SARS-CoV-2 exposure. Therefore, history of river cruise travel should be considered in contact tracing and outbreak investigations.

The prevalence of SARS-CoV-2 infection and long COVID in U.S. adults during the BA.4/BA.5 surge, June-July 2022

Due to changes in SARS-CoV-2 testing practices, passive case-based surveillance may be an increasingly unreliable indicator for monitoring the burden of SARS-CoV-2, especially during surges. We conducted a cross-sectional survey of a population-representative sample of 3042 U.S. adults between June 30 and July 2, 2022, during the Omicron BA.4/BA.5 surge. Respondents were asked about SARS-CoV-2 testing and outcomes, COVID-like symptoms, contact with cases, and experience with prolonged COVID-19 symptoms following prior infection. We estimated the weighted age and sex-standardized SARS-CoV-2 prevalence, during the 14-day period preceding the interview. We estimated age and gender adjusted prevalence ratios (aPR) for current SARS-CoV-2 infection using a log-binomial regression model. An estimated 17.3% (95% CI 14.9, 19.8) of respondents had SARS-CoV-2 infection during the two-week study period-equating to 44 million cases as compared to 1.8 million per the CDC during the same time period. SARS-CoV-2 prevalence was higher among those 18-24 years old (aPR 2.2, 95% CI 1.8, 2.7) and among non-Hispanic Black (aPR 1.7, 95% CI 1.4,2.2) and Hispanic adults (aPR 2.4, 95% CI 2.0, 2.9). SARS-CoV-2 prevalence was also higher among those with lower income (aPR 1.9, 95% CI 1.5, 2.3), lower education (aPR 3.7 95% CI 3.0,4.7), and those with comorbidities (aPR 1.6, 95% CI 1.4, 2.0). An estimated 21.5% (95% CI 18.2, 24.7) of respondents with a SARS-CoV-2 infection >4 weeks prior reported long COVID symptoms. The inequitable distribution of SARS-CoV-2 prevalence during the BA.4/BA.5 surge will likely drive inequities in the future burden of long COVID.

Analysis of daily COVID-19 death bulletin data during the first two waves of the COVID-19 pandemic in Thiruvananthapuram district, Kerala, India

Context

Coronavirus disease 2019 (COVID-19) mortality trends can help discern the pattern of outbreak evolution and systemic responses.

Aim

This study aimed to explore patterns of COVID-19 deaths in Thiruvananthapuram district from 31 March 2020 to 31 December 2021.

Setting and Design

Secondary data analysis of COVID-19 deaths in Thiruvananthapuram district was performed.

Materials and Methods

Mortality data were obtained from the district COVID-19 control room, and deaths in the first and second waves of COVID-19 were compared.

Statistical Analysis

We summarised data as proportions and medians with the inter-quartile range (IQR) and performed Chi-square tests to make comparisons wherever applicable.

Results

As on 31 December 2021, 4587 COVID-19 deaths were reported in Thiruvananthapuram district, with a case fatality rate of 0.91%. We observed high mortality among older persons (66.7%) and men (56.6%). The leading cause of death was bronchopneumonia (60.6%). The majority (88.5%) had co-morbidities, commonly diabetes mellitus (54.9%). The median interval from diagnosis to hospitalisation was 4 days (IQR 2-7), and that from hospitalisation to death was 2 days (IQR 0-6). The deaths reported during the second wave were four times higher than those of the first wave with a higher proportion of deaths in the absence of co-morbidities (p < 0.001). The majority of the deceased were unvaccinated. Ecological analysis with vaccine coverage data indicated 5.4 times higher mortality among unvaccinated than those who received two vaccine doses.

Conclusions

The presence of co-morbidities, an unvaccinated status, and delay in hospitalisation were important reasons for COVID-19 deaths. Primary level health providers can potentially help sustaining vaccination, expeditious referral, and monitoring of COVID-19 patients.

Surveillance for Coccidioidomycosis, Histoplasmosis, and Blastomycosis - United States, 2019

PROBLEM/CONDITION

Coccidioidomycosis, histoplasmosis, and blastomycosis are underdiagnosed fungal diseases that often mimic bacterial or viral pneumonia and can cause disseminated disease and death. These diseases are caused by inhalation of fungal spores that have distinct geographic niches in the environment (e.g., soil or dust), and distribution is highly susceptible to climate changes such as expanding arid regions for coccidioidomycosis, the northward expansion of histoplasmosis, and areas like New York reporting cases of blastomycosis previously thought to be nonendemic. The national incidence of coccidioidomycosis, histoplasmosis, and blastomycosis is poorly characterized.

REPORTING PERIOD

2019.

DESCRIPTION OF SYSTEM

The National Notifiable Diseases Surveillance System (NNDSS) tracks cases of coccidioidomycosis, a nationally notifiable condition reported to CDC by 26 states and the District of Columbia. Neither histoplasmosis nor blastomycosis is a nationally notifiable condition; however, histoplasmosis is voluntarily reported in 13 states and blastomycosis in five states. Health departments classify cases based on the definitions established by the Council of State and Territorial Epidemiologists.

RESULTS

In 2019, a total of 20,061 confirmed coccidioidomycosis, 1,124 confirmed and probable histoplasmosis, and 240 confirmed and probable blastomycosis cases were reported to CDC. Arizona and California reported 97% of coccidioidomycosis cases, and Minnesota and Wisconsin reported 75% of blastomycosis cases. Illinois reported the greatest percentage (26%) of histoplasmosis cases. All three diseases were more common among males, and the proportion for blastomycosis (70%) was substantially higher than for histoplasmosis (56%) or coccidioidomycosis (52%). Coccidioidomycosis incidence was approximately four times higher for non-Hispanic American Indian or Alaska Native (AI/AN) persons (17.3 per 100,000 population) and almost three times higher for Hispanic or Latino persons (11.2) compared with non-Hispanic White (White) persons (4.1). Histoplasmosis incidence was similar across racial and ethnic categories (range: 0.9-1.3). Blastomycosis incidence was approximately six times as high among AI/AN persons (4.5) and approximately twice as high among non-Hispanic Asian and Native Hawaiian or other Pacific Islander persons (1.6) compared with White persons (0.7). More than one half of histoplasmosis (54%) and blastomycosis (65%) patients were hospitalized, and 5% of histoplasmosis and 9% of blastomycosis patients died. States in which coccidioidomycosis is not known to be endemic had more cases in spring (March, April, and May) than during other seasons, whereas the number of cases peaked slightly in autumn (September, October, and November) for histoplasmosis and in winter (December, January, and February) for blastomycosis.

INTERPRETATION

Coccidioidomycosis, histoplasmosis, and blastomycosis are diseases occurring in geographical niches within the United States. These diseases cause substantial illness, with approximately 20,000 coccidioidomycosis cases reported in 2019. Although substantially fewer histoplasmosis and blastomycosis cases were reported, surveillance was much more limited and underdiagnosis was likely, as evidenced by high hospitalization and death rates. This suggests that persons with milder symptoms might not seek medical evaluation and the symptoms self-resolve or the illnesses are misdiagnosed as other, more common respiratory diseases.

PUBLIC HEALTH ACTION

Improved surveillance is necessary to better characterize coccidioidomycosis severity and to improve detection of histoplasmosis and blastomycosis. These findings might guide improvements in testing practices that enable timely diagnosis and treatment of fungal diseases. Clinicians and health care professionals should consider coccidioidomycosis, histoplasmosis, and blastomycosis in patients with community-acquired pneumonia or other acute infections of the lower respiratory tract who live in or have traveled to areas where the causative fungi are known to be present in the environment. Culturally appropriate tailored educational messages might help improve diagnosis and treatment. Public health response to these three diseases is hindered because information gathered from states' routine surveillance does not include data on populations at risk and sources of exposure. Broader surveillance that includes expansion to other states, and more detail about potential exposures and relevant host factors can describe epidemiologic trends, populations at risk, and disease prevention strategies.

Cannabis consumption is associated with lower COVID-19 severity among hospitalized patients: a retrospective cohort analysis

Background

While cannabis is known to have immunomodulatory properties, the clinical consequences of its use on outcomes in COVID-19 have not been extensively evaluated. We aimed to assess whether cannabis users hospitalized for COVID-19 had improved outcomes compared to non-users.

Methods

We conducted a retrospective analysis of 1831 patients admitted to two medical centers in Southern California with a diagnosis of COVID-19. We evaluated outcomes including NIH COVID-19 Severity Score, need for supplemental oxygen, ICU (intensive care unit) admission, mechanical ventilation, length of hospitalization, and in-hospital death for cannabis users and non-users. Cannabis use was reported in the patient’s social history. Propensity matching was used to account for differences in age, body-mass index, sex, race, tobacco smoking history, and comorbidities known to be risk factors for COVID-19 mortality between cannabis users and non-users.

Results

Of 1831 patients admitted with COVID-19, 69 patients reported active cannabis use (4% of the cohort). Active users were younger (44 years vs. 62 years, p < 0.001), less often diabetic (23.2% vs 37.2%, p < 0.021), and more frequently active tobacco smokers (20.3% vs. 4.1%, p < 0.001) compared to non-users. Notably, active users had lower levels of inflammatory markers upon admission than non-users—CRP (C-reactive protein) (3.7 mg/L vs 7.6 mg/L, p < 0.001), ferritin (282 μg/L vs 622 μg/L, p < 0.001), D-dimer (468 ng/mL vs 1140 ng/mL, p = 0.017), and procalcitonin (0.10 ng/mL vs 0.15 ng/mL, p = 0.001). Based on univariate analysis, cannabis users had significantly better outcomes compared to non-users as reflected in lower NIH scores (5.1 vs 6.0, p < 0.001), shorter hospitalization (4 days vs 6 days, p < 0.001), lower ICU admission rates (12% vs 31%, p < 0.001), and less need for mechanical ventilation (6% vs 17%, p = 0.027). Using propensity matching, differences in overall survival were not statistically significant between cannabis users and non-users, nevertheless ICU admission was 12 percentage points lower (p = 0.018) and intubation rates were 6 percentage points lower (p = 0.017) in cannabis users.

Conclusions

This retrospective cohort study suggests that active cannabis users hospitalized with COVID-19 had better clinical outcomes compared with non-users, including decreased need for ICU admission or mechanical ventilation. However, our results need to be interpreted with caution given the limitations of a retrospective analysis. Prospective and observational studies will better elucidate the effects cannabis use in COVID-19 patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42238-022-00152-x.