scholarly journals Natural variability in the disease course of SSc-ILD: implications for treatment

2021 ◽  
Vol 30 (159) ◽  
pp. 200340
Author(s):  
Madelon C. Vonk ◽  
Ulrich A. Walker ◽  
Elizabeth R. Volkmann ◽  
Michael Kreuter ◽  
Sindhu R. Johnson ◽  
...  
Keyword(s):  
Risk Factors ◽  
Topoisomerase I ◽  
Vital Capacity ◽  
Predictive Power ◽  
Risk Scores ◽  
Disease Course ◽  
Progression Risk ◽  
Composite Risk ◽  
Using Data ◽  
Insight Into

Interstitial lung disease (ILD) affects approximately 50% of patients with systemic sclerosis (SSc) and is the leading cause of death in SSc. Our objective was to gain insight into the progression of SSc-associated ILD (SSc-ILD). Using data from longitudinal clinical trials and observational studies, we assessed definitions and patterns of progression, risk factors for progression, and implications for treatment. SSc-ILD progression was commonly defined as exceeding specific thresholds of lung function worsening and/or increasing radiographic involvement. One definition used in several studies is decline in forced vital capacity (FVC) of ≥10%, or ≥5–10% plus a decline in diffusing capacity of the lung for carbon monoxide ≥15%. Based on these criteria, 20–30% of patients in observational cohorts develop progressive ILD, starting early in the disease course and progressing at a highly variable rate.Risk factors such as age, FVC, extent of fibrosis and presence of anti-topoisomerase I antibodies can help predict progression of SSc-ILD, though composite risk scores may offer greater predictive power. Whilst the variability of the disease course in SSc-ILD makes risk stratification of patients challenging, the decision to initiate, change or stop treatment should be based on a combination of the current disease state and the speed of progression.

scholarly journals Prediction of Alzheimer’s disease biomarker status defined by the ‘ATN framework’ among cognitively healthy individuals: results from the EPAD longitudinal cohort study

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Catherine M. Calvin ◽  
◽  
Casper de Boer ◽  
Vanessa Raymont ◽  
John Gallacher ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Blood Pressure ◽  
Alzheimer's Disease ◽  
Family History ◽  
Risk Scores ◽  
Healthy Individuals ◽  
Disease Biomarker ◽  
Composite Risk ◽  
Composite Scores

Abstract Background The Amyloid/Tau/Neurodegeneration (ATN) framework has been proposed as a means of evidencing the biological state of Alzheimer’s disease (AD). Predicting ATN status in pre-dementia individuals therefore provides an important opportunity for targeted recruitment into AD interventional studies. We investigated the extent to which ATN-defined biomarker status can be predicted by known AD risk factors as well as vascular-related composite risk scores. Methods One thousand ten cognitively healthy older adults were allocated to one of five ATN-defined biomarker categories. Multinomial logistic regression tested risk factors including age, sex, education, APOE4, family history of dementia, cognitive function, vascular risk indices (high systolic blood pressure, body mass index (BMI), high cholesterol, physical inactivity, ever smoked, blood pressure medication, diabetes, prior cardiovascular disease, atrial fibrillation and white matter lesion (WML) volume), and three vascular-related composite scores, to predict five ATN subgroups; ROC curve models estimated their added value in predicting pathology. Results Age, APOE4, family history, BMI, MMSE and white matter lesions (WML) volume differed between ATN biomarker groups. Prediction of Alzheimer’s disease pathology (versus normal AD biomarkers) improved by 7% after adding family history, BMI, MMSE and WML to a ROC curve that included age, sex and APOE4. Risk composite scores did not add value. Conclusions ATN-defined Alzheimer’s disease biomarker status prediction among cognitively healthy individuals is possible through a combination of constitutional and cardiovascular risk factors but established dementia composite risk scores do not appear to add value in this context.

scholarly journals A practical approach for geographic prioritization and targeting of insecticide-treated net distribution campaigns during public health emergencies and in resource-limited settings

2022 ◽  
Vol 21 (1) ◽  
Author(s):  
Alyssa J. Young ◽  
Will Eaton ◽  
Matt Worges ◽  
Honelgn Hiruy ◽  
Kolawole Maxwell ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Score ◽  
Value Added ◽  
State Level ◽  
Risk Scores ◽  
Analytic Hierarchy ◽  
Use Of Resources ◽  
Resource Limited ◽  
Geographic Prioritization ◽  
Using Data

Abstract Background The use of data in targeting malaria control efforts is essential for optimal use of resources. This work provides a practical mechanism for prioritizing geographic areas for insecticide-treated net (ITN) distribution campaigns in settings with limited resources. Methods A GIS-based weighted approach was adopted to categorize and rank administrative units based on data that can be applied in various country contexts where Plasmodium falciparum transmission is reported. Malaria intervention and risk factors were used to rank local government areas (LGAs) in Nigeria for prioritization during mass ITN distribution campaigns. Each factor was assigned a unique weight that was obtained through application of the analytic hierarchy process (AHP). The weight was then multiplied by a value based on natural groupings inherent in the data, or the presence or absence of a given intervention. Risk scores for each factor were then summated to generate a composite unique risk score for each LGA. This risk score was translated into a prioritization map which ranks each LGA from low to high priority in terms of timing of ITN distributions. Results A case study using data from Nigeria showed that a major component that influenced the prioritization scheme was ITN access. Sensitivity analysis results indicate that changes to the methodology used to quantify ITN access did not modify outputs substantially. Some 120 LGAs were categorized as ‘extremely high’ or ‘high’ priority when a spatially interpolated ITN access layer was used. When prioritization scores were calculated using DHS-reported state level ITN access, 108 (90.0%) of the 120 LGAs were also categorized as being extremely high or high priority. The geospatial heterogeneity found among input risk factors suggests that a range of variables and covariates should be considered when using data to inform ITN distributions. Conclusion The authors provide a tool for prioritizing regions in terms of timing of ITN distributions. It serves as a base upon which a wider range of vector control interventions could be targeted. Its value added can be found in its potential for application in multiple country contexts, expediated timeframe for producing outputs, and its use of systematically collected malaria indicators in informing prioritization.

Components of metabolic syndrome correlate with longer survival in NSCLC in bexarotene-treated patients with high hypertriglyceridemia in SPIRIT I and II trials: A retrospective analysis

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 7137-7137 ◽  
Author(s):  
Z. Dziewanowska ◽  
J. Zhang ◽  
S. Sun ◽  
E. Groves ◽  
A. Negro-Vilar
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Cox Regression ◽  
Stage Iv ◽  
Risk Scores ◽  
Familial Predisposition ◽  
Cox Regression Analysis ◽  
The Metabolic Syndrome ◽  
Composite Risk ◽  
Nsclc Patients

7137 Background: Bexarotene activates RXR receptors regulating cell proliferation, differentiation, apoptosis and many aspects of lipid metabolism. Both SPIRIT I and II trials (ASCO 2005) showed that a large (36%) subgroup of bexarotene-treated patients showing high sensitivity to hypertriglyceridemia had a significantly longer survival in both studies. This subgroup included males, smokers, stage IV and weight loss, factors associated with poorer survival. A recent study in retinoid-treated patients revealed those developing high hypertriglyceridemia, as well as their parents, have a familial predisposition to hyperlipidemia and the metabolic syndrome (Ann Intern Med, 2002, 136:582). We evaluated baseline and in-treatment patient characteristics in relation to triglyceride responses and overall survival after bexarotene treatment to further extend that observation to NSCLC patients. Methods: A pooled analysis of 595 patients treated with bexarotene in SPIRIT I and II trials assessed factors related to metabolic syndrome (BMI, HDL, LDL and Total cholesterol [T-chol], T-chol/HDL ratio, triglycerides, glucose, blood pressure) at baseline and during treatment at the time of high-triglyceridemia. Individual and composite risk factor scores were evaluated by logistic and Cox-regression analysis in two subgroups, e.g., Responders (high trigs, long survival) and Non-responders (low trigs, shorter survival). Results: Among in-treatment risk factors, Responders (N = 215) had significantly higher (p < 0.0001) BMI, trigs, T-chol, T-chol/HDL ratio and lower HDL (p < 0.0001) than Non-responders (N = 380). A composite risk score (the sum of the individual in-treatment dichotomous risk scores) analysis also showed a significantly (p < 0.0001) higher score for metabolic risk factors in the Responder/longer survival subgroup. Hazard ratio analysis by Cox-regression showed a 13% survival benefit for each composite score increase. Conclusions: Baseline and in-treatment triglycerides and other key metabolic syndrome factors are important predictors and contributors to the beneficial survival impact of bexarotene in this important subgroup of NSCLC patients. [Table: see text]

scholarly journals Eating behaviors moderate the associations between risk factors in the first 1000 days and adiposity outcomes at 6 years of age

2020 ◽  
Vol 111 (5) ◽  
pp. 997-1006
Author(s):  
Anna Fogel ◽  
Keri McCrickerd ◽  
Izzuddin M Aris ◽  
Ai Ting Goh ◽  
Yap-Seng Chong ◽  
...  
Keyword(s):  
Risk Factors ◽  
Eating Behavior ◽  
Risk Score ◽  
Eating Behaviors ◽  
Portion Size ◽  
Breastfeeding Duration ◽  
Risk Scores ◽  
Eating Rate ◽  
Composite Risk ◽  
Food Portions

ABSTRACT Background Several risk factors in the first 1000 d are linked with increased obesity risk in later childhood. The role of potentially modifiable eating behaviors in this association is unclear. Objectives This study examined whether the association between cumulated risk factors in the first 1000 d and adiposity at 6 y is moderated by eating behaviors. Methods Participants were 302 children from the GUSTO (Growing Up in Singapore Towards healthy Outcomes) cohort. Risk factors included maternal prepregnancy and paternal overweight, excessive gestational weight gain, raised fasting plasma glucose during pregnancy, short breastfeeding duration, and early introduction of solid foods. Composite risk scores reflecting the prevalence and the importance of the risk factors present were computed. Adiposity outcomes were child BMI and sum of skinfolds (SSF), and candidate eating behavior moderators were portion size, eating rate, and energy intake during lunch and in an eating in the absence of hunger task. Results Higher composite risk score predicted higher BMI z scores (B = 0.08; 95% CI: 0.04, 0.13) and larger SSF (0.70 mm; 0.23, 1.18 mm), and was associated with larger self-served food portions (5.03 kcal; 0.47, 9.60 kcal), faster eating rates (0.40 g/min; 0.21, 0.59 g/min), and larger lunch intakes (7.05 kcal; 3.37, 10.74 kcal). Importantly, the association between composite risk score and adiposity was moderated by eating behaviors. The composite risk score was unrelated to SSF in children who selected smaller food portions, ate slower, and consumed less energy, but was positively associated with SSF among children who selected larger food portions, ate faster, and consumed more energy (eating behavior × risk score interactions: P &lt; 0.05). Conclusions The association between risk factors in the first 1000 d and adiposity at 6 y varies by eating behaviors, highlighting modifiable behavioral targets for interventions. This trial was registered at clinicaltrials.gov as NCT01174875.

scholarly journals Incorporating Polygenic Risk Scores and Nongenetic Risk Factors for Breast Cancer Risk Prediction among Asian Women, Results from Asia Breast Cancer Consortium

2021 ◽  
Author(s):  
Yaohua Yang ◽  
Ran Tao ◽  
Xiang Shu ◽  
Qiuyin Cai ◽  
Wanqing Wen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Risk Prediction ◽  
Prospective Cohort ◽  
Risk Scores ◽  
Asian Women ◽  
Genome Wide ◽  
Using Data

Importance Polygenic risk scores (PRSs) have shown promises in breast cancer risk prediction; however, limited studies have been conducted among Asian women. Objective To develop breast cancer risk prediction models for Asian women incorporating PRSs and nongenetic risk factors. Design PRSs were developed using data from genome-wide association studies (GWAS) of breast cancer conducted among 123 041 Asian-ancestry women (including 18 650 cases) using three approaches (1) reported PRS for European-ancestry women; (2) breast cancer-associated single-nucleotide polymorphisms (SNPs) identified by fine-mapping of GWAS-identified risk loci; (3) genome-wide risk prediction algorithms. A nongenetic risk score (NgRS) was built including six well-established nongenetic risk factors using data from 1974 Asian women. Integrated risk scores (IRSs) were constructed using PRSs and the NgRS. PRSs were initially validated in an independent dataset including 1426 cases and 1323 controls and further evaluated, along with the NgRS and IRSs, in the second dataset including 368 cases and 736 controls nested withing a prospective cohort study. Setting Case-control and prospective cohort studies. Participants 20 444 breast cancer cases and 106 450 controls from the Asia Breast Cancer Consortium. Main Outcomes and Measures Logistic regression was used to examine associations of risk scores with breast cancer risk to estimate odds ratios (ORs) with 95% confidence intervals (CIs) and area under the receiver operating characteristic curve (AUC). Results In the prospective cohort, PRS111, a PRS with 111 SNPs, developed using the fine-mapping approach showed a prediction performance comparable to a genome-wide PRS including over 855,000 SNPs. The OR per standard deviation increase of PRS111 was 1.67 (95% CI=1.46-1.92) with an AUC of 0.639 (95% CI=0.604-0.674). The NgRS had a limited predictive ability (AUC=0.565; 95% CI=0.529-0.601); while IRS111, the combination of PRS111 and NgRS, achieved the highest prediction accuracy (AUC=0.650; 95% CI=0.616-0.685). Compared with the average risk group (40th-60th percentile), women in the top 5% of PRS111 and IRS111 were at a 3.84-folded (95% CI=2.30-6.46) and 4.25- folded (95% CI=2.57-7.11) elevated risk of breast cancer, respectively. Conclusions and Relevance PRSs derived using breast cancer-associated risk SNPs have similar prediction performance in Asian and European descendants. Including nongenetic risk factors in models further improved prediction accuracy. Our findings support the utility of these models in developing personalized screening and prevention strategies.

Risk Factors for Bleeding during Treatment of Acute Venous Thromboembolism

1996 ◽  
Vol 76 (05) ◽  
pp. 682-688 ◽  
Author(s):  
Jos P J Wester ◽  
Harold W de Valk ◽  
Karel H Nieuwenhuis ◽  
Catherine B Brouwer ◽  
Yolanda van der Graaf ◽  
...  
Keyword(s):  
Risk Factors ◽  
Venous Thromboembolism ◽  
Surface Area ◽  
Body Surface Area ◽  
Body Surface ◽  
Small Body ◽  
Bleeding Risk ◽  
Risk Scores ◽  
Risk Of Bleeding ◽  
Acute Venous Thromboembolism

Summary Objective: Identification of risk factors for bleeding and prospective evaluation of two bleeding risk scores in the treatment of acute venous thromboembolism. Design: Secondary analysis of a prospective, randomized, assessor-blind, multicenter clinical trial. Setting: One university and 2 regional teaching hospitals. Patients: 188 patients treated with heparin or danaparoid for acute venous thromboembolism. Measurements: The presenting clinical features, the doses of the drugs, and the anticoagulant responses were analyzed using univariate and multivariate logistic regression analysis in order to evaluate prognostic factors for bleeding. In addition, the recently developed Utrecht bleeding risk score and Landefeld bleeding risk index were evaluated prospectively. Results: Major bleeding occurred in 4 patients (2.1%) and minor bleeding in 101 patients (53.7%). For all (major and minor combined) bleeding, body surface area ≤2 m2 (odds ratio 2.3, 95% Cl 1.2-4.4; p = 0.01), and malignancy (odds ratio 2.4, 95% Cl 1.1-4.9; p = 0.02) were confirmed to be independent risk factors. An increased treatment-related risk of bleeding was observed in patients treated with high doses of heparin, independent of the concomitant activated partial thromboplastin time ratios. Both bleeding risk scores had low diagnostic value for bleeding in this sample of mainly minor bleeders. Conclusions: A small body surface area and malignancy were associated with a higher frequency of bleeding. The bleeding risk scores merely offer the clinician a general estimation of the risk of bleeding. In patients with a small body surface area or in patients with malignancy, it may be of interest to study whether limited dose reduction of the anticoagulant drug may cause less bleeding without affecting efficacy.

scholarly journals Predicting COVID-19 mortality with electronic medical records

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Hossein Estiri ◽  
Zachary H. Strasser ◽  
Jeffy G. Klann ◽  
Pourandokht Naseri ◽  
Kavishwar B. Wagholikar ◽  
...  
Keyword(s):  
Risk Factors ◽  
Medical Information ◽  
Age Groups ◽  
Prognostic Models ◽  
Smoking History ◽  
Risk Scores ◽  
Gradient Boosting ◽  
Chronic Obstructive ◽  
Clinical Expertise ◽  
History Of

AbstractThis study aims to predict death after COVID-19 using only the past medical information routinely collected in electronic health records (EHRs) and to understand the differences in risk factors across age groups. Combining computational methods and clinical expertise, we curated clusters that represent 46 clinical conditions as potential risk factors for death after a COVID-19 infection. We trained age-stratified generalized linear models (GLMs) with component-wise gradient boosting to predict the probability of death based on what we know from the patients before they contracted the virus. Despite only relying on previously documented demographics and comorbidities, our models demonstrated similar performance to other prognostic models that require an assortment of symptoms, laboratory values, and images at the time of diagnosis or during the course of the illness. In general, we found age as the most important predictor of mortality in COVID-19 patients. A history of pneumonia, which is rarely asked in typical epidemiology studies, was one of the most important risk factors for predicting COVID-19 mortality. A history of diabetes with complications and cancer (breast and prostate) were notable risk factors for patients between the ages of 45 and 65 years. In patients aged 65–85 years, diseases that affect the pulmonary system, including interstitial lung disease, chronic obstructive pulmonary disease, lung cancer, and a smoking history, were important for predicting mortality. The ability to compute precise individual-level risk scores exclusively based on the EHR is crucial for effectively allocating and distributing resources, such as prioritizing vaccination among the general population.

scholarly journals Validation of the adjusted multi-biomarker disease activity score as a prognostic test for radiographic progression in rheumatoid arthritis: a combined analysis of multiple studies

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Jeffrey R. Curtis ◽  
Michael E. Weinblatt ◽  
Nancy A. Shadick ◽  
Cecilie H. Brahe ◽  
Mikkel Østergaard ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disease Activity ◽  
Radiographic Progression ◽  
Protein Biomarkers ◽  
Significant Information ◽  
Disease Activity Measure ◽  
Conventional Dmards ◽  
Risk Curve ◽  
Progression Risk ◽  
Clinical Measures

Abstract Background The multi-biomarker disease activity (MBDA) test measures 12 serum protein biomarkers to quantify disease activity in RA patients. A newer version of the MBDA score, adjusted for age, sex, and adiposity, has been validated in two cohorts (OPERA and BRASS) for predicting risk for radiographic progression. We now extend these findings with additional cohorts to further validate the adjusted MBDA score as a predictor of radiographic progression risk and compare its performance with that of other risk factors. Methods Four cohorts were analyzed: the BRASS and Leiden registries and the OPERA and SWEFOT studies (total N = 953). Treatments included conventional DMARDs and anti-TNFs. Associations of radiographic progression (ΔTSS) per year with the adjusted MBDA score, seropositivity, and clinical measures were evaluated using linear and logistic regression. The adjusted MBDA score was (1) validated in Leiden and SWEFOT, (2) compared with other measures in all four cohorts, and (3) used to generate curves for predicting risk of radiographic progression. Results Univariable and bivariable analyses validated the adjusted MBDA score and found it to be the strongest, independent predicator of radiographic progression (ΔTSS > 5) compared with seropositivity (rheumatoid factor and/or anti-CCP), baseline TSS, DAS28-CRP, CRP SJC, or CDAI. Neither DAS28-CRP, CDAI, SJC, nor CRP added significant information to the adjusted MBDA score as a predictor, and the frequency of radiographic progression agreed with the adjusted MBDA score when it was discordant with these measures. The rate of progression (ΔTSS > 5) increased from < 2% in the low (1–29) adjusted MBDA category to 16% in the high (45–100) category. A modeled risk curve indicated that risk increased continuously, exceeding 40% for the highest adjusted MBDA scores. Conclusion The adjusted MBDA score was validated as an RA disease activity measure that is prognostic for radiographic progression. The adjusted MBDA score was a stronger predictor of radiographic progression than conventional risk factors, including seropositivity, and its prognostic ability was not significantly improved by the addition of DAS28-CRP, CRP, SJC, or CDAI.

scholarly journals Prenatal Sociodemographic Factors Predicting Maltreatment of Children up to 3 Years Old: A Prospective Cohort Study Using Administrative Data in Japan

2021 ◽  
Vol 18 (5) ◽  
pp. 2505
Author(s):  
Aya Isumi ◽  
Kunihiko Takahashi ◽  
Takeo Fujiwara
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Child Maltreatment ◽  
Survey Data ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Characteristic Curve ◽  
Risk Scores ◽  
Prenatal Risk ◽  
Prenatal Risk Factors

Identifying risk factors from pregnancy is essential for preventing child maltreatment. However, few studies have explored prenatal risk factors assessed at pregnancy registration. This study aimed to identify prenatal risk factors for child maltreatment during the first three years of life using population-level survey data from pregnancy notification forms. This prospective cohort study targeted all mothers and their infants enrolled for a 3- to 4-month-old health check between October 2013 and February 2014 in five municipalities in Aichi Prefecture, Japan, and followed them until the child turned 3 years old. Administrative records of registration with Regional Councils for Children Requiring Care (RCCRC), which is suggestive of child maltreatment cases, were linked with survey data from pregnancy notification forms registered at municipalities (n = 893). Exact logistic regression was used for analysis. A total of 11 children (1.2%) were registered with RCCRC by 3 years of age. Unmarried marital status, history of artificial abortion, and smoking during pregnancy were significantly associated with child maltreatment. Prenatal risk scores calculated as the sum of these prenatal risk factors, ranging from 0 to 7, showed high predictive power (area under receiver operating characteristic curve 0.805; 95% confidence interval (CI), 0.660–0.950) at a cut-off score of 2 (sensitivity = 72.7%, specificity = 83.2%). These findings suggest that variables from pregnancy notification forms may be predictors of the risk for child maltreatment by the age of three.

scholarly journals Estimation of the Actual Incidence of Coronavirus Disease (COVID-19) in Emergent Hotspots: The Example of Hokkaido, Japan during February–March 2020

2021 ◽  
Vol 10 (11) ◽  
pp. 2392
Author(s):  
Andrei R. Akhmetzhanov ◽  
Kenji Mizumoto ◽  
Sung-Mok Jung ◽  
Natalie M. Linton ◽  
Ryosuke Omori ◽  
...  
Keyword(s):  
Cumulative Incidence ◽  
Surveillance System ◽  
Negative Binomial ◽  
Actual Number ◽  
Public Health Response ◽  
The Public ◽  
Health Response ◽  
Using Data ◽  
Insight Into ◽  
Actual Incidence

Following the first report of the coronavirus disease 2019 (COVID-19) in Sapporo city, Hokkaido Prefecture, Japan, on 14 February 2020, a surge of cases was observed in Hokkaido during February and March. As of 6 March, 90 cases were diagnosed in Hokkaido. Unfortunately, many infected persons may not have been recognized due to having mild or no symptoms during the initial months of the outbreak. We therefore aimed to predict the actual number of COVID-19 cases in (i) Hokkaido Prefecture and (ii) Sapporo city using data on cases diagnosed outside these areas. Two statistical frameworks involving a balance equation and an extrapolated linear regression model with a negative binomial link were used for deriving both estimates, respectively. The estimated cumulative incidence in Hokkaido as of 27 February was 2,297 cases (95% confidence interval (CI): 382–7091) based on data on travelers outbound from Hokkaido. The cumulative incidence in Sapporo city as of 28 February was estimated at 2233 cases (95% CI: 0–4893) based on the count of confirmed cases within Hokkaido. Both approaches resulted in similar estimates, indicating a higher incidence of infections in Hokkaido than were detected by the surveillance system. This quantification of the gap between detected and estimated cases helped to inform the public health response at the beginning of the pandemic and provided insight into the possible scope of undetected transmission for future assessments.

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