Pandemics have been considered among the main hazards of two last decades around the world. Hospitals are one of the most important organizations responding to pandemics. Aim of this study was to design and develop a valid checklist for evaluating the hospitals’ performance in response to COVID-19 pandemic, for the first time.

This study is a mixed method research design that began in 2020 February and was conducted in three phases: Designing a conceptual model, designing a primary checklist structure, and checklist psychometric evaluation. Known groups method has been used to evaluate construct validity. Therefore, two groups of hospital were compared; (group A: COVID-19 Hospitals, and group B: the other Hospitals).

The main structure of checklist was designed with 6 main domains, 23 sub-domains, and 152 items. The content validity ratio and index were 0.94 and 0.79 respectively. Eleven items were added, 106 items were removed, and 40 items were edited. Independent t-test showed a significant difference between scores of two groups of hospitals (P<0.0001). Pearson correlation coefficient test also showed a high correlation between our checklist and the other. The internal consistency of the checklist was 0.98 according to Cronbach’s alpha test.

By evaluating the hospitals’ performance and identifying their strengths and weaknesses, can help health system policymakers and hospital managers, and leads to improved performance in response to COVID-19.

This study aimed to identify the roles of community pharmacists (CPs) during the coronavirus disease 2019 (COVID-19) pandemic, the differences in their role performance compared with their perceived importance, and limiting factors.

A cross-sectional online survey of CPs was conducted. The CPs self-measured the importance and performance of each role during the pandemic using a five-point Likert scale. A paired t-test was used to compare each role’s importance and performance scores. A logistic regression analysis of the roles with low performance scores, despite their level of importance, was conducted to determine the factors affecting performance. The limiting factors were also surveyed.

The 436 responses to the questionnaire were analyzed. The performance scores were significantly lower than the perceived importance scores for 15 of the 17 roles. The source and update frequency of COVID-19 information and participation in outreach pharmaceutical services were associated with low performance scores. Insufficient economic compensation, the lack of communication channels, and legal limitations were the limiting factors in performing the CPs’ roles.

The participation in outreach pharmaceutical services, economic compensation, and communication channel should be improved to motivate the CPs in performing their roles.

The increased threat of natural disasters makes understanding the relationship between community resources and children’s mental health critical. Mental health care efficacy and access are crucial to assessing the quality of community mental health care availability.

The primary objective of this scoping review is to investigate the relationship between children’s mental health and community mental health resource efficacy and accessibility after a major disaster

Conducted a systematic search to identify epidemiologic and health service utilization studies assessing the relationship between disasters and subsequent health service utilization amongst children and adolescents.

The research returned 1682 potentially relevant studies and 31 articles were selected based on identified criteria from pre-selected databases.

The studies conclude a gender and age-based disparity in access and efficiency of children’s mental health services. The studies also identify the need for greater resource distribution and organizational structure.

Monoclonal antibody (mAb) treatment for COVID-19 has been underutilized due to logistical challenges, lack of access and variable treatment awareness among patients and healthcare professionals. The use of telehealth during the pandemic provides an opportunity to increase access to COVID-19 care.

This is a single-center descriptive study of telehealth-based patient self-referral for mAb therapy between March 1, 2021, to October 31, 2021 at Baltimore Convention Center Field Hospital (BCCFH).

Among the 1001 self-referral patients, the mean age was 47, and most were female (57%) white (66%), and had a primary care provider (62%). During the study period, self-referrals increased from 14 per month in March to 427 in October resulting in a 30-fold increase. About 57% of self-referred patients received a telehealth visit, and of those 82% of patients received mAb infusion therapy. The median time from self-referral to onsite infusion was 2 days (1-3 IQR).

Our study shows the integration of telehealth with a self-referral process improved access to mAb infusion. A high proportion of self-referrals were appropriate and led to timely treatment. This approach helped those without traditional avenues for care and avoided potential delay for patients seeking referral from their PCPs.

Food security during public health emergencies relies on situational awareness of needs and resources. Artificial intelligence (AI) has revolutionized situational awareness during crises, allowing the allocation of resources to needs through machine learning algorithms. Limited research exists monitoring Twitter for changes in the food security-related public discourse during the COVID-19 pandemic. We aim to address that gap with AI by classifying food security topics on Twitter and showing topic frequency per day.

Tweets were scraped from Twitter from January 2020 through December 2021 using food security keywords. Latent Dirichlet Allocation (LDA) topic modeling was performed, followed by time-series analyses on topic frequency per day.

237,107 tweets were scraped and classified into topics, including food needs and resources, emergency preparedness and response, and mental/physical health. After the WHO’s pandemic declaration, there were relative increases in topic density per day regarding food pantries, food banks, economic and food security crises, essential services, and emergency preparedness advice. Threats to food security in Tigray emerged in 2021.

AI is a powerful yet underused tool to monitor food insecurity on social media. Machine learning tools to improve emergency response should be prioritized, along with measurement of impact. Further food insecurity word patterns testing, as generated by this research, with supervised machine learning models can accelerate the uptake of these tools by policymakers and aid organizations.