Characteristics of Patients with Hematologic Malignancies Without Seroconversion Post-COVID19 Third Vaccine Dosing (preprint)

Patients with hematologic malignancies (HM) are at greater risk of severe morbidity and mortality caused by COVID19 and show a lower response to a two-dose COVID19 mRNA vaccine series. The primary objective of this retrospective cohort study is to explore the characteristics of the subset of patients with HM who had little to no change in SARS-CoV-2 spike antibody titer levels after a 3rd vaccine dose (3V) (-/-). As a secondary objective, we seek to compare the cohorts of patients who did and did not seroconvert post-3V to get a better understanding of the demographics and potential drivers of serostatus. A total of 625 patients with HM had two titer results at least 21 days apart pre- and post- the 3V dose. Among the participants who were seronegative prior to 3V (268), 149 (55.6%) seroconverted after the 3V dose and 119 (44.4%) did not. HM diagnosis was significantly associated with seroconversion status (P = .0003) with patients non-Hodgkin lymphoma 6 times the odds of not seroconverting compared to multiple myeloma patients (P = .0010). Among the cohort of patients who remained seronegative post-3V, 107 (90.0%) patients showed no reaction to 3V as indicated by pre- and post- 3V index values. This study focuses on an important subset of patients with HM who are not seroconverting after the COVID mRNA 3V, providing much needed data for clinicians to target and counsel this subset of patients.

Which urban communities are susceptible to COVID-19? An empirical study through the lens of community resilience.

BACKGROUND: After the lockdown of Wuhan on January 23, 2020, the government used community-based pandemic prevention and control as the core strategy to fight the pandemic, and explored a set of standardized community pandemic prevention measures that were uniformly implemented throughout the city. One month later, the city announced its first lists of "high-risk" communities and COVID-19-free communities. Under the standardized measures of pandemic prevention and mitigation, why some communities showed a high degree of resilience and effectively avoided escalation, while the situation spun out of control in other communities? This study investigated: 1) key factors that affect the effective response of urban communities to the pandemic, and 2) types of COVID-19 susceptible communities. METHODS: This study employs the crisp-set qualitative comparative analysis method to explore the influencing variables and possible causal condition combination paths that affect community resilience during the pandemic outbreak. Relying on extreme-case approach, 26 high-risk communities and 14 COVID-19 free communities were selected as empirical research subjects from the lists announced by Wuhan government. The community resilience assessment framework that evaluates the communities' capacity on pandemic prevention and mitigation covers four dimensions, namely spatial resilience, capital resilience, social resilience, and governance resilience, each dimension is measured by one to three variables. RESULTS: The results of measuring the necessity of 7 single-condition variables found that the consistency index of "whether the physical structure of the community is favorable to virus transmission" reached 0.9, which constitutes a necessary condition for COVID-19 susceptible communities. By analyzing the seven condition configurations with high row coverage and unique coverage in the obtained complex solutions and intermediate solutions, we found that outbreaks are most likely to occur in communities populated by disadvantaged populations. However, if lacking spatial-, capital-, and governance resilience, middle-class and even wealthy communities could also become areas where COVID-19 spreads easily. CONCLUSIONS: Three types of communities namely vulnerable communities, alienated communities, and inefficient communities have lower risk resilience. Spatial resilience, rather than social resilience, constitutes the key influencing factor of COVID-19-susceptible communities, and the dual deficiencies of social resilience and governance resilience are the common features of these communities.