Effect of pooled tracheal sample testing on the probability of Mycoplasma hyopneumoniae detection.

Tracheal pooling for Mycoplasma hyopneumoniae (M. hyopneumoniae) DNA detection allows for decreased diagnostic cost, one of the main constraints in surveillance programs. The objectives of this study were to estimate the sensitivity of pooled-sample testing for the detection of M. hyopneumoniae in tracheal samples and to develop probability of M. hyopneumoniae detection estimates for tracheal samples pooled by 3, 5, and 10. A total of 48 M. hyopneumoniae PCR-positive field samples were pooled 3-, 5-, and 10-times using field M. hyopneumoniae DNA-negative samples and tested in triplicate. The sensitivity was estimated at 0.96 (95% credible interval [Cred. Int.]: 0.93, 0.98) for pools of 3, 0.95 (95% Cred. Int: 0.92, 0.98) for pools of 5, and 0.93 (95% Cred. Int.: 0.89, 0.96) for pools of 10. All pool sizes resulted in PCR-positive if the individual tracheal sample Ct value was < 33. Additionally, there was no significant decrease in the probability of detecting at least one M. hyopneumoniae-infected pig given any pool size (3, 5, or 10) of tracheal swabs. Furthermore, this manuscript applies the probability of detection estimates to various real-life diagnostic testing scenarios. Combining increased total animals sampled with pooling can be a cost-effective tool to maximize the performance of M. hyopneumoniae surveillance programs.

Pioneering a Multi-Phase Framework to Harmonize Self-Reported Sleep Data Across Cohorts.

STUDY OBJECTIVES: Harmonizing and aggregating data across studies enable pooled analyses that support external validation and enhance replicability and generalizability. However, the multidimensional nature of sleep poses challenges for data harmonization and aggregation. Here we describe and implement our process for harmonizing self-reported sleep data. METHODS: We established a multi-phase framework to harmonize self-reported sleep data: (1) compile items; (2) group items into domains; (3) harmonize items; and (4) evaluate harmonizability. We applied this process to produce a pooled multi-cohort sample of five United States cohorts plus a separate yet fully harmonized sample from Rotterdam, Netherlands. Sleep and sociodemographic data are described and compared to demonstrate the utility of harmonization and aggregation. RESULTS: We collected 190 unique self-reported sleep items and grouped them into 15 conceptual domains. Using these domains as guiderails, we developed 14 harmonized items measuring aspects of Satisfaction, Alertness/Sleepiness, Timing, Efficiency, Duration, Insomnia, and Sleep Apnea. External raters determined that 13 of these 14 items had moderate-to-high harmonizability. Alertness/Sleepiness items had lower harmonizability, while continuous, quantitative items (e.g., timing, total sleep time, efficiency) had higher harmonizability. Descriptive statistics identified features that are more consistent (e.g., wake-up time, duration) and more heterogeneous (e.g., time in bed, bedtime) across samples. CONCLUSIONS: Our process can guide researchers and cohort stewards towards effective sleep harmonization and provides a foundation for further methodological development in this expanding field. Broader national and international initiatives promoting common data elements across cohorts are needed to enhance future harmonization and aggregation efforts.

Employee Sleep Promotion Programs in Workplace Settings: An Exciting, Viable Area for Lifestyle Medicine.

In the past several decades, our population sleep health has fallen short of recommendations. Moreover, there has been an increase in sleep difficulties amidst COVID-19. Work consumes a huge proportion of our waking lives, and the nature of our work can impact the quantity and quality of employee sleep. Conversely, employee sleep also matters for work-related outcomes as evidence demonstrates poor employee sleep health is associated with increased presenteeism, absenteeism, and health care costs. Given the prevalence of poor sleep health in our population, the changing nature of work and increasing demands on capped time, the worksite represents a promising and potentially underexplored venue for lifestyle medicine practitioners to consider employee sleep health and, where possible, novel employee sleep health promotion programs. This article outlines the impact of work on sleep and reviews the potential for incorporating sleep into lifestyle interventions in workplace settings.

Association of Chronotype and Shiftwork with COVID-19 Infection.

OBJECTIVE: This study assesses whether chronotype is related to COVID-19 infection and whether there is an interaction with shift work. METHODS: Cross-sectional survey of 19,821 U.S. adults. RESULTS: COVID-19 infection occurred in 40% of participants, 32.6% morning and 17.2% evening chronotypes. After adjusting for demographic and socioeconomic factors, shift/remote work, sleep duration and comorbidities, morning chronotype was associated with a higher (aOR: 1.15, 95% CI 1.10-1.21) and evening chronotype with a lower (aOR: 0.82, 95% CI: 0.78-0.87) prevalence of COVID-19 infection in comparison to an intermediate chronotype. Working exclusively night shifts was not associated with higher prevalence of COVID-19. Morning chronotype and working some evening shifts was associated with the highest prevalence of previous COVID-19 infection (aOR: 1.87, 95% CI: 1.28-2.74). CONCLUSION: Morning chronotype and working a mixture of shifts increase risk of COVID-19 infection.

Estimating Community Disruption from Nighttime Gunshots in 6 U.S. Cities, 2015 to 2021.

BACKGROUND: Gunshots affect those directly involved in an incident and those in the surrounding community. The community-level impact of nighttime gunshots, which may be particularly disruptive to the sleep of nearby community members, is unknown. OBJECTIVE: Our aim is to estimate the number of people potentially affected by nighttime gunshots and the relationship between nighttime gunshots and median household income in the USA. DESIGN: We collected publicly available data on the timing and location of gunshots in six U.S. cities (Baltimore, MD; Boston, MA; Washington, D.C.; New York, NY; Philadelphia, PA; and Portland, OR) from 2015 to 2021. We then analyzed the data by computing rate ratios (RRs) to compare the frequency of gunshots during nighttime hours (6:00 pm to 5:59 am) versus daytime hours (6:00 am to 5:59 pm). Additionally, we used geospatial mapping to create choropleth maps to visualize the variation in nighttime gunshot density across cities. We estimated, using city-wide population, person-nights potentially impacted by the sound of gunshots within areas of 0.2- (low) and 0.5-mile (high) radius. Finally, for five of six cities where data on median household income were available by census tract, we built nonlinear regression models to estimate the relationship between the number of nighttime gunshots and median household income. KEY RESULTS: We analyzed 72,236 gunshots. Gunshots were more common during the nighttime than daytime (overall RR = 2.5). Analyses demonstrated that the low estimates for the mean annual number of person-nights impacted by nighttime gunshots were 0.4 million in Baltimore and Portland, 1.3 million in Philadelphia, 1.6 million in Boston, 2.9 million in New York City, and 5.9 million in Washington. The number of nighttime gunshots was inversely related to median household income. CONCLUSIONS: Nighttime gunshots are prevalent, particularly in low-income neighborhoods, and may have under-recognized effects on the surrounding community.

Sleep Apnea and Incident Stroke in a National Cohort of Black and White Adults.

BACKGROUND AND OBJECTIVES: Racial/ethnic differences have been documented in the relationship between obstructive sleep apnea (OSA) and stroke incidence, yet racial differences in OSA symptoms or treatment and their relationship with stroke incidence are underexplored and may contribute to stroke disparities. We comprehensively examined OSA symptoms and their relationships to stroke incidence by race/ethnicity. METHODS: Data were collected from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study, a population-based cohort of Black and White individuals in the United States. Participants free from a stroke diagnosis at baseline were included. Participants self-reported the following: (1) snoring; (2) daytime sleepiness; (3) provider-diagnosed sleep apnea (PDSA); and (4) treatment for PDSA using positive airway pressure (PAP). OSA risk was categorized as high or low based on the Berlin Sleep Questionnaire. Incident stroke was defined as first occurrence of stroke over an average of 12 (SD 3.9) years of follow-up. We report the relationships between snoring, OSA risk, PDSA, PAP therapy use, and incident stroke by race/ethnicity using Cox proportional hazards models after adjusting for demographic and socioeconomic factors and stroke risk factors. RESULTS: Among the 22,192 participants (mean age [SD] 64.2[9.1] years), 38.1% identified as Black. Overall, snoring was not associated with incident stroke (hazard ratio [HR] 0.98, 95% CI 0.85-1.13). However, among White individuals but not Black individuals, high OSA risk and PDSA were associated with incident stroke (HR 1.22, 95% CI 1.01-1.47; HR 1.33, 95% CI 1.04-1.70, respectively). PAP therapy use among those with PDSA (compared with non-PDSA) was associated with incident stroke in White individuals (HR 1.38, 95% CI 1.05-1.80). PAP therapy use among those with PDSA (compared with those with PDSA without PAP therapy use) was associated with reduced risk of incident stroke in Black (HR 0.39, 95% CI 0.17-0.91) but not White (HR 0.63, 95% CI 0.37-1.10) individuals. DISCUSSION: White individuals with high OSA risk and those with PDSA with or without PAP therapy use were at increased incident stroke risk, whereas Black individuals reporting PDSA and PAP had reduced incident stroke risk relative to those not using PAP. Future research is needed to understand the mechanisms underlying racial differences in OSA and stroke such as differences in assessment modes and treatment.

Association of Obstructive Sleep Apnea with Post-Acute Sequelae of SARS-CoV-2 Infection.

BACKGROUND: Obstructive sleep apnea is associated with COVID-19 infection. Less clear is whether obstructive sleep apnea is a risk factor for the development of post-acute sequelae of SARS-CoV-2 infection (PASC). STUDY DESIGN: Cross-sectional survey of a general population of 24,803 US adults to determine the association of obstructive sleep apnea with PASC. RESULTS: COVID-19 infection occurred in 10,324 (41.6%) participants. Prevalence of persistent (>3 months post infection) putative PASC-related physical and mental health symptoms ranged from 6.5% (peripheral edema) to 19.6% (nervous/anxious). In logistic regression models, obstructive sleep apnea was associated with all putative PASC-related symptoms with the highest adjusted odds ratios being fever (2.053) and nervous/anxious (1.939). In 4 logistic regression models of overall PASC derived from elastic net regression, obstructive sleep apnea was associated with PASC (range of adjusted odds ratios: 1.934-2.071); this association was mitigated in those with treated obstructive sleep apnea. In the best fitting overall model requiring ≥3 symptoms, PASC prevalence was 21.9%. CONCLUSION: In a general population sample, obstructive sleep apnea is associated with the development of PASC-related symptoms and a global definition of PASC. Treated obstructive sleep apnea mitigates the latter risk. The presence of 3 or more PASC symptoms may be useful in identifying cases and for future research.

Animal drug shortages limit veterinary therapeutic options and introduce artifacts in antimicrobial sales reporting.

Supply chain issues disrupt veterinary care and cause downstream consequences that alter the practice of veterinary medicine. Antimicrobials are just 1 class of pharmaceuticals that have been impacted by supply chain issues over the last couple of years. Since February 2021, 2 sponsors/manufacturers of penicillin products have reported shortages in the active pharmaceutical ingredient. With the release of the 2021 Summary Report on Antimicrobials Sold or Distributed for Use in Food-Producing Animals by the FDA, a key finding was a 19% decrease in penicillin sales and distribution from 2020 to 2021. Herein, we provide our clinicians' professional perspective regarding how drug shortages, specifically that of penicillin, might contribute to misconstrued patterns in antimicrobial use and what can be done by veterinarians and the FDA to minimize the impact of an antimicrobial drug shortage on animal health and well-being.

Musings on messages and mediums: How communication and marketing techniques can aid in sleep health promotion.

Health communication theory and methods offer promise for anyone interested in translating sleep and circadian findings into population sleep outcomes. Health communication research includes planning, implementation, and evaluation activities, and examining beliefs, behaviors, and environmental factors unique to the target audience; selecting appropriate medium for message dissemination; and crafting a captivating message to nudge a person or population toward better sleep health. Opportunities for leveraging health communication tools for advancing sleep and circadian health are explored.

Public opinion of resident physician work hours in 2022.

OBJECTIVE: The purpose of this study was to characterize public awareness and opinion regarding resident physician work hours in the United States. METHODS: We conducted a nationally representative cross-sectional survey among adults in the United States. Demographic quota-based sampling was conducted by Qualtrics to match 2020 United States Census estimates of age, sex, race, and ethnicity. Descriptive statistics are presented. Hypothesis testing was conducted to identify characteristics associated with agreement with current resident physician work-hour policies. RESULTS: 4763 adults in the United States participated in the study. 97.1% of the public believes that resident physicians should not work 24-hour shifts and 95.6% believe the current 80 hours resident work week is too long. 66.4% of the participants reported that the maximum shift duration should be 12 consecutive hours or fewer, including 22.9% who recommended a maximum shift length of 8 hours. Similarly, 66.4% reported that maximum weekly work hours should be 59 or fewer, including 24.9% who recommended a maximum of 40 weekly work hours. CONCLUSIONS: Nearly all US adults disagree with current work-hour policies for resident physicians. Public opinion supports limiting shifts to no more than 12 consecutive hours and weekly work to no more than 60 hours, which is in sharp contrast to current regulations that permit of 28 hours shifts and 80 hours of work per week.

Characterizing Gun Violence by Time, Day of the Week, Holidays, and Month in 6 US Cities, 2015-2021.

Developing interventions to prevent firearm-related violence and to address its consequences requires an improved understanding of when these violent events are most likely to occur. We explored gunshot events in 6 of the most populated cities in the United States by time of day, day of week, holiday/non-holiday, and month using publicly available datasets. In some of these cities, gunshot events occurred most often at nighttime, on holidays and weekends, and during summer months, with significant interaction effects. There were also time-related changes in characteristics of the victims. Primary prevention efforts aimed at curbing firearm-related violence should consider these differential risks.

Sleep and mental health among unpaid caregivers of children, adults, and both: United States, 2022.

OBJECTIVES: We sought to characterize sleep and mental health, and their relationship, among unpaid caregivers. METHODS: During March through August 2022, four waves of cross-sectional surveys were administered to US adults using demographic quota sampling and weighting to improve representativeness of the US adult population. RESULTS: Among 19,767 respondents, 6260 (31.7%) identified as serving one or more unpaid caregiving roles. Compared to people without caregiving roles, caregivers more commonly reported sleep duration outside the healthy range (7-9 hours), insomnia symptoms, diagnosed sleep disorders, and more commonly screened positive for anxiety, depression, and burnout symptoms. Multivariable analyses adjusted for demographics characteristics revealed unpaid caregivers had several-fold elevated odds of adverse mental health symptoms; associations were attenuated but remained significant after adjusting for impaired and nonoptimal sleep. CONCLUSIONS: Both sleep and mental health challenges are disproportionately experienced by and commonly co-occur among unpaid caregivers, especially those who care for both children and adults. These populations, which serve critical societal roles, may benefit from enhanced support services to address sleep and mental health.

The organization of sleep-wake patterns around daily schedules in college students.

Time is a zero-sum game, and consequently, sleep is often sacrificed for waking activities. For college students, daily activities, comprised of scheduled classes, work, study, social and other extracurricular events, are major contributors to insufficient and poor-quality sleep. We investigated the impact of daily schedules on sleep-wake timing in 223 undergraduate students (age: 18-27 years, 37% females) from a United States (U.S.) university, monitored for approximately 30 days. Sleep-wake timing and daily recorded activities (attendance at academic, studying, exercise-based and/or extracurricular activities) were captured by a twice-daily internet-based diary. Wrist-worn actigraphy was conducted to confirm sleep-wake timing. Linear mixed models were used to quantify associations between daily schedule and sleep-wake timing at between-person and within-person levels. Later schedule start time predicted later sleep onset (between and within: p<.001), longer sleep duration on the previous night (within: p<.001), and later wake time (between and within: p<.001). Later schedule end time predicted later sleep onset (between: p<.05, within: p<.001) and shorter sleep duration that night (within: p<.001). For every 1 hour that recorded activities extended beyond 10pm, sleep onset was delayed by 15 minutes at the within-person level and 45 minutes at the between-person level, and sleep duration was shortened by 5 and 23 minutes, respectively. Increased daily documented total activity time predicted earlier wake (between and within: p<.001), later sleep onset that night (within: p<.05), and shorter sleep duration (within: p<.001). These results indicate that daily schedules are an important factor in shaping sleep timing and duration in college students.

Infection prediction in swine populations with machine learning.

The pork industry is an essential part of the global food system, providing a significant source of protein for people around the world. A major factor restraining productivity and compromising animal wellbeing in the pork industry is disease outbreaks in pigs throughout the production process: widespread outbreaks can lead to losses as high as 10% of the U.S. pig population in extreme years. In this study, we present a machine learning model to predict the emergence of infection in swine production systems throughout the production process on a daily basis, a potential precursor to outbreaks whose detection is vital for disease prevention and mitigation. We determine features that provide the most value in predicting infection, which include nearby farm density, historical test rates, piglet inventory, feed consumption during the gestation period, and wind speed and direction. We utilize these features to produce a generalizable machine learning model, evaluate the model's ability to predict outbreaks both seven and 30 days in advance, allowing for early warning of disease infection, and evaluate our model on two swine production systems and analyze the effects of data availability and data granularity in the context of our two swine systems with different volumes of data. Our results demonstrate good ability to predict infection in both systems with a balanced accuracy of [Formula: see text] on any disease in the first system and balanced accuracies (average prediction accuracy on positive and negative samples) of [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] on porcine reproductive and respiratory syndrome, porcine epidemic diarrhea virus, influenza A virus, and Mycoplasma hyopneumoniae in the second system, respectively, using the six most important predictors in all cases. These models provide daily infection probabilities that can be used by veterinarians and other stakeholders as a benchmark to more timely support preventive and control strategies on farms.

Gaps in Parental Understanding of Sleep Disturbances During Maintenance Therapy for Pediatric Acute Lymphoblastic Leukemia.

Background: Acute lymphoblastic leukemia (ALL) is the most common cancer in childhood, with survival rates approaching 90%. Sleep disturbance is common among ALL patients, often developing during the initial stages of chemotherapy treatment. While there have been significant efforts to understand and intervene in this issue during survivorship, there is far less research on children who are actively receiving treatment. In the current study, we sought to better understand the parent's experience in the sleep domain during maintenance therapy, including their perceptions of how their child's medical team had managed sleep disturbances, and recommendations for how to improve sleep management. Method: Fifteen parents of pediatric ALL patients (aged 4-12 years) completed semistructured interviews. Interview content was analyzed using a multistage thematic analysis. Results: Parents consistently expressed feeling unprepared to manage the sleep disruptions that arose during treatment, often reporting that they did not recall being told this would be a side effect. They were enthusiastic about learning how to improve their child's sleep, though they did not want pharmacotherapeutic interventions or additional medical/psychosocial appointments to address this. Conclusion: Despite consistent provider communication on sleep, parents report limited knowledge of the issue. This provides an obvious intervention target to improve treatment-related sleep disturbances. Clear messaging may help direct parents' attention and expectations regarding their child's treatment and potential for disturbed sleep, possibly in the form of a behavioral intervention that empowers parents with information about how to support their child's sleep health while they are undergoing treatment for ALL.

Association of Chronotype and Shiftwork with COVID-19 Infection.

Objective: This study assesses whether chronotype is related to COVID-19 infection and whether there is an interaction with shift work. Methods: Cross-sectional survey of 19,821 U.S. adults. Results: COVID-19 infection occurred in 40% of participants, 32.6% morning and 17.2% evening chronotypes. After adjusting for demographic and socioeconomic factors, shift work, sleep duration and comorbidities, morning chronotype was associated with a higher (aOR: 1.15, 95% CI 1.10-1.21) and evening chronotype with a lower (aOR: 0.82, 95% CI: 0.78-0.87) prevalence of COVID-19 infection in comparison to an intermediate chronotype. Working exclusively night shifts was not associated with higher prevalence of COVID-19. Morning chronotype and working some evening shifts was associated with the highest prevalence of previous COVID-19 infection (aOR: 1.87, 95% CI: 1.28-2.74). Conclusion: Morning chronotype and working a mixture of shifts increase risk of COVID-19 infection.

Associations between obstructive sleep apnea and COVID-19 infection and hospitalization among US adults.

STUDY OBJECTIVES: Medical comorbidities increase the risk of severe COVID-19 infection. In some studies, obstructive sleep apnea (OSA) has been identified as a comorbid condition that is associated with an increased prevalence of COVID-19 infection and hospitalization, but few have investigated this association in a general population. This study aimed to answer the following research question: In a general population, is OSA associated with increased odds of COVID-19 infection and hospitalization and are these altered with COVID-19 vaccination? METHODS: This was a cross-sectional survey of a diverse sample of 15,057 US adults. RESULTS: COVID-19 infection and hospitalization rates in the cohort were 38.9% and 2.9%, respectively. OSA or OSA symptoms were reported in 19.4%. In logistic regression models adjusted for demographic, socioeconomic, and comorbid medical conditions, OSA was positively associated with COVID-19 infection (adjusted odds ratio: 1.58, 95% CI: 1.39-1.79) and COVID-19 hospitalization (adjusted odds ratio: 1.55, 95% CI: 1.17-2.05). In fully adjusted models, boosted vaccination status was protective against both infection and hospitalization. Boosted vaccination status attenuated the association between OSA and COVID-19 related hospitalization but not infection. Participants with untreated or symptomatic OSA were at greater risk for COVID-19 infection; those with untreated but not symptomatic OSA were more likely to be hospitalized. CONCLUSIONS: In a general population sample, OSA is associated with a greater likelihood of having had a COVID-19 infection and a COVID-19 hospitalization with the greatest impact observed among persons experiencing OSA symptoms or who were untreated for their OSA. Boosted vaccination status attenuated the association between OSA and COVID-19-related hospitalization. CITATION: Quan SF, Weaver MD, Czeisler MÉ, et al. Associations between obstructive sleep apnea and COVID-19 infection and hospitalization among U.S. adults. J Clin Sleep Med. 2023;19(7):1303-1311.

Mobile Apps for Dietary and Food Timing Assessment: Evaluation for Use in Clinical Research.

BACKGROUND: Over the last decade, health mobile apps have become an increasingly popular tool used by clinicians and researchers to track food consumption and exercise. However, many consumer apps lack the technological features for facilitating the capture of critical food timing details. OBJECTIVE: This study aimed to introduce users to 11 apps from US app stores that recorded both dietary intake and food timing to establish which one would be the most appropriate for clinical research. METHODS: To determine a viable app that recorded both dietary intake and food timing for use in a food timing-related clinical study, we evaluated the time stamp data, usability, privacy policies, the accuracy of nutrient estimates, and general features of 11 mobile apps for dietary assessment that were available on US app stores. The following apps were selected using a keyword search of related terms and reviewed: text entry apps-Cronometer, DiaryNutrition, DietDiary, FoodDiary, Macros, and MyPlate; image entry apps-FoodView and MealLogger; and text plus image entry apps-Bitesnap, myCircadianClock, and MyFitnessPal. RESULTS: Our primary goal was to identify apps that recorded food time stamps, which 8 (73%) of the 11 reviewed apps did. Of the 11 apps, only 4 (36%) allowed users to edit the time stamps. Next, we sought to evaluate the usability of the apps using the System Usability Scale across 2 days, and 82% (9/11) of the apps received favorable scores for usability. To enable use in research and clinical settings, the privacy policies of each app were systematically reviewed using common criteria, with 1 (9%) Health Insurance Portability and Accountability Act-compliant app (Cronometer). Furthermore, protected health information was collected by 9 (82%) of the 11 apps. Finally, to assess the accuracy of the nutrient estimates generated by these apps, we selected 4 sample food items and a 3-day dietary record to input into each app. The caloric and macronutrient estimates of the apps were compared with the nutrient estimates provided by a registered dietitian using the Nutrition Data System for Research database. In terms of the 3-day food record, the apps were found to consistently underestimate daily calories and macronutrients compared with the Nutrition Data System for Research output. CONCLUSIONS: Overall, we found that the Bitesnap app provided flexible dietary and food timing functionality capable of being used in research and clinical settings, whereas most other apps lacked in the necessary food timing functionality or user privacy.

Predicting antimicrobial resistance of bacterial pathogens using time series analysis.

Antimicrobial resistance (AMR) is arguably one of the major health and economic challenges in our society. A key aspect of tackling AMR is rapid and accurate detection of the emergence and spread of AMR in food animal production, which requires routine AMR surveillance. However, AMR detection can be expensive and time-consuming considering the growth rate of the bacteria and the most commonly used analytical procedures, such as Minimum Inhibitory Concentration (MIC) testing. To mitigate this issue, we utilized machine learning to predict the future AMR burden of bacterial pathogens. We collected pathogen and antimicrobial data from >600 farms in the United States from 2010 to 2021 to generate AMR time series data. Our prediction focused on five bacterial pathogens (Escherichia coli, Streptococcus suis, Salmonella sp., Pasteurella multocida, and Bordetella bronchiseptica). We found that Seasonal Auto-Regressive Integrated Moving Average (SARIMA) outperformed five baselines, including Auto-Regressive Moving Average (ARMA) and Auto-Regressive Integrated Moving Average (ARIMA). We hope this study provides valuable tools to predict the AMR burden not only of the pathogens assessed in this study but also of other bacterial pathogens.