Objective: We utilized national claims-based data to identify the change in hazard of diagnosis of ALS following a possible ALS-related diagnosis (e.g., falls) and whether the change in hazard varies whether the patient lives in an urban or rural area. Methods: Health insurance claims data from both the commercial insurance market and Medicare supplemental market were obtained from the Merative MarketScan Commercial Claims and Encounters and Medicare Coordination of Benefits databases. Individuals with a diagnosis of ALS were identified and matched on age, sex, and enrollment period to individuals without ALS. For all individuals, inciting events such as falls, muscle related symptoms, or bulbar symptoms were also extracted. We then used fixed-effects regression to estimate the risk of being diagnosed with ALS following one of these events controlling for urban-rural status. Additionally, we utilized interaction terms to evaluate the effect of rurality on odds of diagnosis. Results: 19,126 individuals with ALS were included with 96,126 controls. Patients with ALS were more likely than matched controls to live in an urban area (87 vs 85%). Of those with ALS 84% had a symptom code preceding their diagnosis as compared to 51% in the general population. The association between having any symptoms and future diagnosis of ALS remained statistically significant after adjustment for confounders and an odds ratio of nearly 5. Odds ratios for the individual symptoms varied from 1.2 to over 10. In all models, living in an urban area was associated with increased odds of diagnosis with ALS while the effect of having a symptom was smaller among urban dwellers. Urban dwellers who are diagnosed with ALS are diagnosed at younger ages. Conclusions: Early diagnosis of ALS is vital for connecting patients with research and treatment options. These results suggest symptoms appear in the administrative health record potentially years before the diagnosis of ALS. Additionally, rural patients are diagnosed at later ages with a greater dependence on major symptoms than urban patients. These results highlight potential improvements for surveillance and screening for ALS.

Determining whether SARS-CoV-2 exhibits seasonality like other respiratory viruses is critical for public health planning. We evaluated whether COVID-19 rates follow a seasonal pattern using time series models. We used time series decomposition to extract the annual seasonal component of COVID-19 case, hospitalization, and mortality rates from March 2020 through December 2022 for the United States and Europe. Models were adjusted for a country-specific stringency index to account for confounding by various interventions. Despite year-round disease activity, we identified seasonal spikes in COVID-19 from approximately November through April for all outcomes and in all countries. Our results support employing annual preventative measures against SARS-CoV-2, such as administering seasonal booster vaccines in a similar timeframe as those in place for influenza. Whether certain high-risk individuals may need more than one COVID-19 vaccine booster dose each year will depend on factors like vaccine durability against severe illness and levels of year-round disease activity.

Importance: Acute appendicitis is a common cause of abdominal pain and the most common reason for emergency surgery in several countries. Increased cases during summer months have been reported.

Objective: To investigate the incidence of acute appendicitis by considering local temperature patterns in geographic regions with different climate over several years.

Design, Setting, and Participants: This cohort study used insurance claims data from the MarketScan Commercial Claims and Encounters Database and the Medicare Supplemental and Coordination of Benefits Database from January 1, 2001, to December 31, 2017. The cohort included individuals at risk for appendicitis who were enrolled in US insurance plans that contribute data to the MarketScan databases. Cases of appendicitis in the inpatient, outpatient, and emergency department settings were identified using International Classification of Diseases, Ninth Revision, Clinical Modification or International Statistical Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes. Local weather data were obtained for individuals living in a metropolitan statistical area (MSA) from the Integrated Surface Database. Associations were characterized using a fixed-effects generalized linear model based on a negative binomial distribution. The model was adjusted for age, sex, and day of week and included fixed effects for year and MSA. The generalized linear model was fit with a piecewise linear model by searching each 0.56 °C in temperature for change points. To further isolate the role of temperature, observed temperature was replaced with the expected temperature and the deviation of the observed temperature from the expected temperature for a given city on a given day of year. Data were analyzed from October 1, 2021, to July 31, 2022.

Main Outcomes and Measures: The primary outcome was the daily number of appendicitis cases in a given city stratified by age and sex, with mean temperature in the MSA over the previous 7 days as the independent variable.

Results: A total of 450 723 744 person-years at risk and 689 917 patients with appendicitis (mean (SD) age, 35 (18) years; 347 473 male (50.4%) individuals) were included. Every 5.56 °C increase in temperature was associated with a 1.3% increase in the incidence of appendicitis (incidence rate ratio (IRR), 1.01; 95% CI, 1.01-1.02) when temperatures were 10.56 °C or lower and a 2.9% increase in incidence (IRR, 1.03; 95% CI, 1.03-1.03) for temperatures higher than 10.56 °C. In terms of temperature deviations, a higher-than-expected temperature increase greater than 5.56 °C was associated with a 3.3% (95% CI, 1.0%-5.7%) increase in the incidence of appendicitis compared with days with near-0 deviations.

Conclusions and Relevance: Results of this cohort study observed seasonality in the incidence of appendicitis and found an association between increased incidence and warmer weather. These results could help elucidate the mechanism of appendicitis.