Perceptions of COVID-19 Vaccination among Organ Transplant Recipients (preprint)

Understanding vaccine hesitancy in organ transplant recipients (OTR) is critical, given clear, alt-hough attenuated, benefits from vaccination. Adult OTR were surveyed regarding vaccine-related values and a novel outcome variable called Vaccine Acceptance Composite Score (VACS) was built as the average Likert score of 7 domains of vaccination confidence. Of 46 OTR included (93.5% kidney transplant recipients), 32.6% were female, 13.3% Black, 6.77% Hispan-ic/Latino/a/x; median age was 58 years. Patients were most concerned about COVID-19 vac-cine-associated risks (46.3%), its potential effect on allograft (47.6%) and motives of government officials involved with vaccine policy (55.6%). Politically conservative patients were likely to have a significantly lower VACS, while those who lived with someone ≥65 had a higher VACS. The VACS was not significantly associated with race, income, religious beliefs, comorbidities, COVID-19 history, or influenza vaccination status. Higher VACS was significantly associated with ≥3 and ≥4 COVID-19 immunizations. This study highlighted political beliefs and elderly household members as correlates of vaccine acceptance among OTR. The VACS may be a useful tool to help standardize multifaceted analyses in vaccination-focused behavioral research, as well as identify individuals and groups at risk for vaccine hesitancy, who may benefit from tai-lored outreach and educational interventions.

The Psychological Ability to Cope Reduced Infections During the Pandemic: A Two-Year Population-Based Study of The Determinants of 123 Million COVID-19 Test Results in Denmark (preprint)

During the COVID-19 pandemic, a key concern for authorities was to identify and activate the psychological states most likely to motivate the public to engage in protective behavior such as physical distancing and hygienic protection. While feelings of fear and threat were rampant during the pandemic, theories of health psychology have highlighted appraisals related to the ability to cope (e.g., the feeling of being able to cost-effectively adhere to government advice) and argued that coping appraisals are superior predictors of motivations to protect the self against risks. In this study, we provide a massive population-based comparison of the association between, on the one hand, threat appraisals, and coping appraisals and, on the other hand, protection against actual infection during the COVID-19 pandemic. To this end, we utilize a unique data infrastructure from Denmark that couple surveys of 8 % of the adult Danish population (N= 386.633) with the individual results of all 123 million COVID-19 tests performed in Denmark during 23 months of the COVID-19 pandemic. Overall, controlling for a comprehensive range of sociodemographic measures and employing panel data to bolster internal validity, we observe that stronger coping appraisals are consistently associated with lower individual probability of COVID-19 infection risk. We find no con-sistent evidence for a similar association for threat appraisals. Threat appraisals rather seem to index – to some extent, accurately – individual feelings of infection exposure. As appeals to fear also have unintended negative consequences (includ-ing anxiety, fatigue, and stigmatization), the findings provide strong empirical support for relying on coping-oriented public health communication in future societal crises in the domain of health and beyond.

Retrospective Analysis of Clostridioides difficile Infection Rates in Hospitalized Patients during COVID-19 Pandemic. A Unicenter Study in Reus, Spain (preprint)

.Background: Clostridioides difficile infections (CDI) vary in severity from mild diarrhea to life-threatening conditions like pseudomembranous colitis or toxic megacolon, often leading to sepsis and death. The COVID-19 pandemic prompted changes in healthcare practices, potentially affecting CDI incidence, though reported data are inconclusive. We studied factors influencing CDI incidence and outcomes at a university hospital throughout the COVID-19 pandemic years. Methods: We conducted a retrospective study on all adult hospitalized CDI cases from January 1, 2020, to December 31, 2022. We collected demographic information, comorbid conditions, and concurrent infections. Results: While overall CDI and COVID-19 rates decreased in 2022, a nota-ble increase in CDI infections was observed among oncological patients and those undergoing some aggressive treatments, such as colon or gastroscopies. The prevalence of comorbidities remained unmodified, and there were declines in prior gastrointestinal surgeries and proton pump inhibitor prescriptions. Factors associated with patient fatality or prolonged hospitaliza-tion included older age, cancer, chronic kidney disease, higher Charlson and McCabe indices, elevated C-reactive protein, and low albumin concentrations. Conclusion: Our study shows the evolving landscape of CDI during the COVID-19 pandemic and emphasizes the impact of de-layed diagnoses and treatments exacerbated by telemedicine adoption. Identified risk factors for CDI-related mortality or prolonged hospital stays underscore the importance of targeted inter-ventions in high-risk populations.

Saving High-Risk Patients from COVID-19 Severity and Death Mainly with Plant-Based Diets and Supplements (preprint)

Our report presents the findings from a treatment program that involved plant-based diets (PBDs) and supplements for 1,750 elderly cardiology patients diagnosed with COVID-19 between April 2020 and June 2023. At the start of the program, there was no published data supporting the use of PBDs for COVID-19 patients. However, after 18 months, studies were released that indicated the effectiveness of PBDs in decreasing the incidence and severity of COVID-19. Our treatment protocol differed from these studies in several ways. We carefully controlled the quality, quantity, and processing method of the foods we provided, opting for raw instead of cooked vegetables. Additionally, we incorporated supplementation that complemented the nutrients lacking in a PBD and enhanced the anti-viral, anti-inflammatory, antioxidant, antithrombotic, and immunomodulatory properties of a PBD. Our patients recovered faster (12±1.4 days vs. 20.9±4.3 days), with lower severity (2% vs. 10-20%), hospitalizations (0 vs. 5-10%), and deaths (0 vs. 15-17%) compared to the general population. These favorable outcomes are particularly noteworthy given Indonesia's high COVID-19 morbidity and mortality rates, among the highest in Asia. The findings of this report provide valuable insights for practitioners in managing high-risk elderly COVID-19 patients, particularly in avoiding severity and mortality.

SARS-CoV-2 spike S2 subunit inhibits p53 activation of p21(WAF1), TRAIL Death Receptor DR5 and MDM2 proteins in cancer cells (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and COVID-19 infection has led to worsened outcomes for patients with cancer. SARS-CoV-2 spike protein mediates host cell infection and cell-cell fusion that causes stabilization of tumor suppressor p53 protein. In-silico analysis previously suggested that SARS-CoV-2 spike interacts with p53 directly but this putative interaction has not been demonstrated in cells. We examined the interaction between SARS-CoV-2 spike, p53 and MDM2 (E3 ligase, which mediates p53 degradation) in cancer cells using an immunoprecipitation assay. We observed that SARS-CoV-2 spike protein interrupts p53-MDM2 protein interaction but did not detect SARS-CoV-2 spike bound with p53 protein in the cancer cells. We further observed that SARS-CoV-2 spike suppresses p53 transcriptional activity in cancer cells including after nutlin exposure of wild-type p53-, spike S2-expressing tumor cells and inhibits chemotherapy-induced p53 gene activation of p21(WAF1), TRAIL Death Receptor DR5 and MDM2. The suppressive effect of SARS-CoV-2 spike on p53-dependent gene activation provides a potential molecular mechanism by which SARS-CoV-2 infection may impact tumorigenesis, tumor progression and chemotherapy sensitivity. In fact, cisplatin-treated tumor cells expressing spike S2 were found to have increased cell viability as compared to control cells. Further observations on gamma-H2AX expression in spike S2-expressing cells treated with cisplatin may indicate altered DNA damage sensing in the DNA damage response pathway. The preliminary observations reported here warrant further studies to unravel the impact of SARS-CoV-2 and its various encoded proteins including spike on pathways of tumorigenesis and response to cancer therapeutics.

Precision medicine for pandemics: stratification of COVID-19 molecular phenotypes defined by topological analysis of global blood gene expression. (preprint)

Precision medicine offers a promising avenue for better therapeutic responses to pandemics such as COVID-19. This study leverages independent patient cohorts in Florence and Liege gathered under the umbrella of the DRAGON consortium for the stratification of molecular phenotypes associated with COVID-19 using topological analysis of global blood gene expression. Whole blood from 173 patients was collected and RNA was sequenced on the Novaseq platform. Molecular phenotypes were defined through topological analysis of gene expression relative to the biological network using the TopMD algorithm. The two cohorts from Florence and Liege allowed for independent validation of the findings in this study. Clustering of the topological maps of differential pathway activation revealed three distinct molecular phenotypes of COVID-19 in the Florence patient cohort, which were also observed in the Liege cohort. Cluster 1, was characterised by high activation of pathways associated with ESC pluripotency, NRF2, and TGF-B; receptor signalling. Cluster 2 displayed high activation of pathways including focal adhesion-PI3K-Akt-mTOR signalling and type I interferon induction and signalling, while Cluster 3 exhibited low IRF7-related pathway activation. TopMD was also used with the Drug-Gene Interaction Database (DGIdb), revealing pharmaceutical interventions targeting mechanisms across multiple phenotypes and individuals. The data illustrates the utility of molecular phenotyping from topological analysis of blood gene expression, and holds promise for informing personalised therapeutic strategies not only for COVID-19 but also for Disease X. Its potential transferability across multiple diseases highlights the value in pandemic response efforts, offering insights before large-scale clinical studies are initiated.

Exploring the Spatial Distribution of Persistent SARS-CoV-2 Mutations - Leveraging mobility data for targeted sampling (preprint)

Given the rapid cross-country spread of SARS-CoV-2 and the resulting difficulty in tracking lineage spread, we investigated the potential of combining mobile service data and fine-granular metadata (such as postal codes and genomic data) to advance integrated genomic surveillance of the pandemic in the federal state of Thuringia, Germany. We sequenced over 6,500 SARS-CoV-2 Alpha genomes (B.1.1.7) across seven months within Thuringia while collecting patients' isolation dates and postal codes. Our dataset is complemented by over 66,000 publicly available German Alpha genomes and mobile service data for Thuringia. We identified the existence and spread of nine persistent mutation variants within the Alpha lineage, seven of which formed separate phylogenetic clusters with different spreading patterns in Thuringia. The remaining two are sub-clusters. Mobile service data can indicate these clusters' spread and highlight a potential sampling bias, especially of low-prevalence variants. Thereby, mobile service data can be used either retrospectively to assess surveillance coverage and efficiency from already collected data or to actively guide part of a surveillance sampling process to districts where these variants are expected to emerge. The latter concept proved successful as we introduced a mobility-guided sampling strategy for the surveillance of Omicron sublineage BQ.1.1. The combination of mobile service data and SARS-CoV-2 surveillance by genome sequencing is a valuable tool for more targeted and responsive surveillance.

The asymptomatic proportion of SARS-CoV-2 Omicron-variant infections in households: A systematic review (preprint)

Background Understanding the clinical spectrum of SARS-CoV-2 infection, including the asymptomatic fraction, is important as asymptomatic individuals are still able to infect other individuals and contribute to ongoing transmission. The WHO Unity Household transmission investigation (HHTI) protocol provides a platform for the prospective and systematic collection of high-quality clinical, epidemiological, serological, and virological data from SARS-CoV-2 confirmed cases and their household contacts. These data can be used to understand key severity and transmissibility parameters - including the asymptomatic proportion - in relation to local epidemic context and help inform public health response. Methods We aimed to estimate the asymptomatic proportion of SARS-CoV-2 Omicron-variant infections in Unity-aligned HHTIs. We conducted a systematic review and meta-analysis in alignment with the PRISMA 2020 guidelines and registered our systematic review on PROSPERO (CRD42022378648). We searched EMBASE, Web of Science, MEDLINE, and bioRxiv and medRxiv from 1 November 2021 to 22 August 2023. Results We identified 8,368 records, of which 98 underwent full text review. We identified only three studies for data extraction, with substantial variation in study design and corresponding estimates of the asymptomatic proportion. As a result, we did not generate a pooled estimate or I2 metric. Conclusions The limited number of quality studies that we identified highlights the need for improved preparedness and response capabilities to facilitate robust HHTI implementation, analysis and reporting, to better inform national, regional and global risk assessments and policy making.

Physical activity, low-grade inflammation, and psychological responses to the COVID-19 pandemic among older adults in England (preprint)

Mental health responses to the COVID-19 pandemic have been widely studied, but less is known about the potentially protective role of physical activity (PA) and the impact of low-grade inflammation. Using a sample of older adults from England, this study tested (1) if pre-pandemic PA and its changes during the pandemic were associated with mental health responses; (2) if older adults with low-grade inflammation experienced greater increases in depression and anxiety, compared to pre-pandemic levels; (3) if PA attenuated the association between inflammation and depression/anxiety. The study used data from the English Longitudinal Study of Ageing, a cohort study following a national sample aged 50+. Information on mental health and PA were collected before the pandemic (2016/17 and 2018/19) and during November and December 2020. Inflammation was ascertained using pre-pandemic C-reactive protein (CRP). Analyses were adjusted for sociodemographic and health-related factors and pre-pandemic mental health. Increasing PA from before to during the pandemic was linked to reduced odds of depression (OR = 0.955, 95%CI [0.937, 0.974]) and anxiety (OR = 0.954, 95%CI [0.927; 0.982]). Higher pre-pandemic PA was associated with reduced odds of depression (OR = 0.964, 95%CI [0.948, 0.981]) and anxiety (OR = 0.976, 95%CI [0.953, 1.000]), whereas elevated CRP was associated with 1.343 times higher odds of depression (95%CI [1.100, 1.641]). PA did not attenuate the inflammation-depression association. The findings suggest that PA may contribute to psychological resilience among older adults, independently of inflammation. Further research is needed to explore the psychobiological pathways underlying this protective mechanism.

Precision Phenotyping for Curating Research Cohorts of Patients with Post-Acute Sequelae of COVID-19 (PASC) as a Diagnosis of Exclusion (preprint)

Scalable identification of patients with the post-acute sequelae of COVID-19 (PASC) is challenging due to a lack of reproducible precision phenotyping algorithms and the suboptimal accuracy, demographic biases, and underestimation of the PASC diagnosis code (ICD-10 U09.9). In a retrospective case-control study, we developed a precision phenotyping algorithm for identifying research cohorts of PASC patients, defined as a diagnosis of exclusion. We used longitudinal electronic health records (EHR) data from over 295 thousand patients from 14 hospitals and 20 community health centers in Massachusetts. The algorithm employs an attention mechanism to exclude sequelae that prior conditions can explain. We performed independent chart reviews to tune and validate our precision phenotyping algorithm. Our PASC phenotyping algorithm improves precision and prevalence estimation and reduces bias in identifying Long COVID patients compared to the U09.9 diagnosis code. Our algorithm identified a PASC research cohort of over 24 thousand patients (compared to about 6 thousand when using the U09.9 diagnosis code), with a 79.9 percent precision (compared to 77.8 percent from the U09.9 diagnosis code). Our estimated prevalence of PASC was 22.8 percent, which is close to the national estimates for the region. We also provide an in-depth analysis outlining the clinical attributes, encompassing identified lingering effects by organ, comorbidity profiles, and temporal differences in the risk of PASC. The PASC phenotyping method presented in this study boasts superior precision, accurately gauges the prevalence of PASC without underestimating it, and exhibits less bias in pinpointing Long COVID patients. The PASC cohort derived from our algorithm will serve as a springboard for delving into Long COVID's genetic, metabolomic, and clinical intricacies, surmounting the constraints of recent PASC cohort studies, which were hampered by their limited size and available outcome data.

Effects of the Covid-19 pandemic on the continuity of sexual and reproductive health care in the maternity ward of a health and social promotion centre in Burkina Faso: a qualitative study (preprint)

The COVID-19 pandemic has significantly impacted the continuity of maternity care in Burkina Faso. This study aimed to compare the volumes of in-person visits and explore the experiences of healthcare providers and users regarding the continuity of healthcare in the maternity ward of a Health and Social Promotion Center (HSPC) before, during, and after the lockdown during the COVID-19 pandemic in Ouagadougou, Burkina Faso. Methods We conducted a multimethod, cross-sectional exploratory study with a phenomenological approach. Monthly health administrative data regarding family planning visits, antenatal visits, deliveries, and postnatal care before, during, and after COVID-19 were collected and compared. Qualitative data were collected through semi-structured interviews with family healthcare providers and users and thematically analyzed. Results The study found that the pandemic led to a decline in the demand for healthcare, as people were afraid of contracting COVID-19. This was particularly true for pregnant women who had recently given birth. The study also found that the pandemic disrupted the supply of essential medicines and medical supplies, which made it difficult for healthcare providers to provide quality care. The qualitative analysis allowed us to highlight three themes: the representation of respondents on COVID-19, their perception of the effectiveness of barrier measures and their analysis of the continuity of care in times of COVID-19: the picture of respondents on COVID-19, their perception of the efficacy of barrier measures and their analysis of the continuity of care in times of COVID-19. Despite these challenges, the study found that healthcare providers and users could find ways to maintain continuity of care. Conclusion The study concludes that the COVID-19 pandemic has significantly impacted the continuity of maternity care in Burkina Faso. However, healthcare providers and users have found ways to maintain continuity of care, and the study provides recommendations for improving continuity of care in the future.

Completeness of the COVID-19 Vaccination Schedule among Persons Experiencing Homelessness in Brazil (preprint)

Almost four years after COVID-19 was declared a global health emergency, equitable distribution of the vaccine remains a challenge, especially among homeless people, the fastest growing population in Brazil. Therefore, we sought to identify the factors associated with completion of the COVID-19 vaccination schedule among homeless people in Brazil. Materials and Methods: We carried out a cross-sectional study in the capital cities of Brazil's Federative Units, considering people living on the streets as the target population. We used a sequential inclusion approach, with individual interviews conducted by trained professionals, using a validated questionnaire. We used descriptive statistics to analyze the data and a binary logistic regression model to identify factors associated with homeless individuals who completed the COVID-19 vaccination schedule. Results: It was identified that the highest density of homeless people and indicators related to COVID-19 is located in the Northeast, Southeast and South regions of Brazil. The primary data sample consisted of 1,392 participants, predominantly male (n: 961; 69.0%), with an average age of 38.3±15.2 years, belonging to the black/brown race/color (n: 1,097; 78.8%), with an elementary school education (n: 1,060; 76.1%). The factors associated with completing the vaccination schedule were: receiving government aid (OR: 1.58; 95%CI: 1.09 - 2.30), visits from Health Agents from the Street Clinic (OR: 3.19; 95%CI: 1.95 - 5.36), history of COVID-19 (OR: 5.77; 95%CI: 3.17 - 11.15), support for mandatory vaccination against COVID-19 (OR: 3.76; 95%CI: 2.48 - 5.76), trust in the efficacy of vaccines (OR: 3.92; 95%CI: 2.63 - 5.89), seeking information from NGOs, street clinics, community leaders (OR: 1.91; 95%CI: 1.01 - 3.88) and trust in the Federal Government's statements on vaccines (OR: 1.57; 95%CI: 1.06 - 2.31).Conclusion: The study advances knowledge by highlighting the completeness of the COVID-19 vaccination schedule among the homeless population. The source of information proved to be one of the determinants of completeness, and the Unified Health System played a leading role in raising awareness among homeless people, notably through its strategy of street clinics, when available. The evidence points to the importance of affirmative and inclusive actions that guarantee access to the vaccine for homeless people.

SARS-CoV-2 Antigen Rapid Detection Tests: test performance during the COVID-19 pandemic and the impact of COVID-19 vaccination (preprint)

IntroductionDuring the COVID-19 pandemic, SARS-CoV-2 antigen rapid detection tests (RDTs) emerged as point-of-care diagnostics in addition to the RT-qPCR as the gold standard for SARS-CoV-2 diagnostics. Facing the course of the COVID-19 pandemic to an endemic characterised by several SARS-CoV-2 virus variants of concern (VOC) and an increasing public COVID-19 vaccination rate the aim of the study was to investigate the long-term test performance of SARS-CoV-2 RDT in large-scale, clinical screening use during and its influencing factors, above all SARS-CoV-2 VOC and COVID-19 vaccination. MethodsIn a prospective performance assessment conducted at a single centre tertiary care hospital, RDTs from three manufacturers (NADAL(R), Panbio, MEDsan(R)) were compared to RT-qPCR among individuals aged [≥] 6 month. The evaluation involved the determination of standardised viral load from oropharyngeal swabs as well as the evaluation of their influencing factors, especially the COVID-19 vaccination, for detecting SARS-CoV-2 in a clinical point-of-care environment spanning from 12 November 2020 to 30 June 2023 among patients, staff, and visitors of the hospital. ResultsAmong the 78,798 RDT/RT-qPCR tandems analysed, 2,016 (2.6%) tandems tested positive for SARS-CoV-2, with an overall sensitivity of 34.5% (95% CI 32.4-36.6%). A logistic regression revealed that typical COVID-19 symptoms significantly declined over the course of the study and throughout the COVID-19 pandemic, and that among the vaccinated, significantly fewer presented with an infection exhibiting typical symptoms. The employed lasso regression model indicated that only higher viral load and typical COVID-19 symptoms significantly increase the likelihood of a positive RDT result in the case of a SARS-CoV-2 infection directly. ConclusionOur findings indicate that only viral load and COVID-19 symptoms directly influence RDT performance while the obtained effects of COVID-19 vaccination and Omicron VOC both reducing RDT performance were mediated by these two factors. RDTs remain an adequate diagnostic tool for detecting SARS-CoV-2 in individuals showing respiratory symptoms. RDTs show promise beyond SARS-CoV-2, proving adaptable for detecting other pathogens like Influenza and RSV, highlighting their ongoing importance in infection control and prevention efforts.

Psychosocial Predictors of Sleep Disturbances during COVID-19: differential contributions of demographic, psychological, pandemic-related factors to sleep health. (preprint)

Aim: Since the declaration of COVID-19 as a Public Health Emergency of International Concern on January 30, 2020, the disease escalated into a global pandemic forcing governments around the world to impose measures that affected all aspects of life. Among other countries, Greece adopted social restriction, lockdowns, and quarantines to reduce transmission from person to person.  Subjects and Methods: This cross-sectional study aimed to investigate the impact of those measures on sleep health in a Greek adult sample. An online questionnaire collected data during from 650 participant.  Results: 60% of responders scored below the clinical cut-off on the RU-SATED, indicating they experienced poor sleep health. Better sleep health was reported with increased age and years of education. On the other hand, higher trauma-related distress, depression, anxiety and stress symptomatology were related to poorer sleep health. No gender differences were observed, and degree of compliance to pandemic restrictions did not influence sleep health. Hierarchical regression analysis indicated difficulty in securing enough/healthy food, testing positive for COVID-19, experiencing an increase in verbal arguments/conflicts at home and an increase in responsibilities were the strongest predictors of poor sleep heath.  Conclusions: Results highlight the importance of maintaining good sleep health as a pillar of general physical and mental health.

Exploring the Perspectives of Clients and Clinicians Regarding Digitally Delivered Psychotherapies Utilized for Trauma-Affected Populations. (preprint)

During the COVID-19 pandemic, many clinical sites shifted towards digital delivery of mental health services. However, there is still much to learn regarding tailoring interventions for trauma-affected populations, including military members, Veterans, and public safety personnel. This study examined perceptions of psychotherapies utilized for trauma-affected populations, as reported by Canadian military members, Veterans, and public safety personnel who completed such interventions and mental health clinicians who provided them. Specifically, we explored the shift to digital health use, what changed with this rapid shift, what needs, problems, and solutions arose, and important future considerations associated with delivering trauma-focused and adjunct treatments digitally.   Quantitative survey data were collected from 11 Canadian patients (military members, Veterans, and public safety personnel with post-traumatic stress injury) and 12 Canadian mental health clinicians. Survey questions were adapted from the Alberta Quality Matrix for Health (AQMH) and Unified Theory of Acceptance and Use of Technology (UTAUT) model. As a follow-up, participants were invited to participate in either a semi-structured qualitative interview or focus group to further explore their perspectives on digitally delivered trauma-focused and adjunct therapies. Four clients and 19 clinician participants participated in an interview or focus group.   In survey and interview/focus group results, patient and clinician participants reported that digitally delivered trauma and adjunct therapies offered similar treatment effectiveness as in-person delivery while also improving treatment access. Participants indicated unique advantages of digital delivery, including the increased accessibility of treatment, cost effectiveness, and more efficient use of resources. However, some participants struggled with using digital platforms and felt less comfortable working in a digital environment. Further research with a larger, more diverse population is required to corroborate our results and identify other avenues in which psychotherapies utilized for trauma-affected populations can be engaged with and improved upon.

Early detection of disease outbreaks and non-outbreaks using incidence data (preprint)

Forecasting the occurrence and absence of novel disease outbreaks is essential for disease management. Here, we develop a general model, with no real-world training data, that accurately forecasts outbreaks and non-outbreaks. We propose a novel framework, using a feature-based time series classification method to forecast outbreaks and non-outbreaks. We tested our methods on synthetic data from a Susceptible-Infected-Recovered model for slowly changing, noisy disease dynamics. Outbreak sequences give a transcritical bifurcation within a specified future time window, whereas non-outbreak (null bifurcation) sequences do not. We identified incipient differences in time series of infectives leading to future outbreaks and non-outbreaks. These differences are reflected in 22 statistical features and 5 early warning signal indicators. Classifier performance, given by the area under the receiver-operating curve, ranged from 0.99 for large expanding windows of training data to 0.7 for small rolling windows. Real-world performances of classifiers were tested on two empirical datasets, COVID-19 data from Singapore and SARS data from Hong Kong, with two classifiers exhibiting high accuracy. In summary, we showed that there are statistical features that distinguish outbreak and non-outbreak sequences long before outbreaks occur. We could detect these differences in synthetic and real-world data sets, well before potential outbreaks occur.