Twitter is a useful source for detecting anti-vaccine content due to the increasing prevalence of these arguments on social media. We aimed to identify the prominent themes about vaccine hesitancy and refusal on social media posts in Turkish during the COVID-19 pandemic. In this qualitative study, we collected public tweets (n = 551,245) that contained a vaccine-related keyword and had been published between 9 December 2020 and 8 January 2021 through the Twitter API. A random sample of tweets (n = 1041) was selected and analyzed by four researchers with the content analysis method. We found that 90.5% of the tweets were about vaccines, 22.6% (n = 213) of the tweets mentioned at least one COVID-19 vaccine by name, and the most frequently mentioned COVID-19 vaccine was CoronaVac (51.2%). We found that 22.0% (n = 207) of the tweets included at least one anti-vaccination theme. Poor scientific processes (21.7%), conspiracy theories (16.4%), and suspicions towards manufacturers (15.5%) were the most frequently mentioned themes. The most co-occurring themes were “poor scientific process” with “suspicion towards manufacturers” (n = 9), and “suspicion towards health authorities” (n = 5). This study may be helpful for health managers, assisting them to identify the major concerns of the population and organize preventive measures through the significant role of social media in early spread of information about vaccine hesitancy and anti-vaccination attitudes.

Background: Vaccine hesitation, which is defined as one of the most important global health threats by World Health Organization, maintains its universal importance during the COVID-19 period. Due to the increasing appearance of anti-vaccine arguments on social media, Twitter is a useful resource in detecting these contents. In this study, we aimed to identify the prominent themes about vaccine hesitancy and refusal on social media during the COVID-19 pandemic. Methods: In this qualitative study we collected Twitter contents which contain a vaccine-related keywords and published publicly between 9/12/2020 and 8/1/2021 (n=551,245). A stratified random sample (n=1041) is selected and analyzed by four researchers with content analysis method. Results: All tweets included in the study were shared from 1,000 unique accounts of which 2.7% were verified and 11.3% organizational users. 90.5% of the tweets were about vaccines, 22.6% (n=213) of the tweets mentioned at least one COVID-19 vaccine name and the most frequently mentioned COVID-19 vaccine was CorronaVac (51.2%). Yet, it was mostly as "Chinese vaccine" (42.3%). 22.0% (n=207) of the tweets included at least one anti-vaccination theme. Among tweets that included an anti-vaccination theme; poor scientific processes (21.7%), conspiracy theories (16.4%), and suspicions towards manufacturers (15.5%) were the most frequently mentioned themes. The most co-occurred themes were "Poor scientific process" theme come along with "suspicion towards manufacturers" (n=9) and "suspicion towards health authorities" (n=5). Conclusions: This study may be helpful for health managers to identify the major concerns of the population and organize the preventive measures, through the significant role of social media on early information about vaccine hesitancy and anti-vaccination attitudes.

The aim of the study is, evaluation of the pandemic data of and measures taken by 20 countries with the highest reported number of cases in the first 100 days of the pandemic, in terms of demographic data and healthcare resources. Materials and Methods: The data used in the study were obtained from ECDC, OECD and Oxford COVID-19 Government Response Tracker. The countries were categorized into two groups, early-onset and late-onset countries, in terms of their date of first confirmed cases and Stringency Index (SI) were calculated. Results: United States has the highest number of cases (432,132). France was the first country to report death, outside of China. Top three countries with the highest Case Fatality Rate (CFR) are France (13.25), Italy (12.67) and United Kingdom (11.69). There was a strong negative correlation between "total death/total population proportion" and the intensive care unit bed per million population (r=-0.720; p= 0.008). The ''proportion of ≥65 age'' was found to have a moderately positive correlation with "total case / total population proportion" as well as "total death / total population proportion" (r= 0.687; p= 0.001; r= 0.635; p= 0.003, respectively). In the late-onset countries, the logarithmic growth of both case and death numbers is faster than the early-onset countries. The SI is higher in late-onset counties both on the dates of logarithmic growth in the number of cases and on the 100th day of the pandemic. Restrictions on international travel is the earliest measure taken by countries. Turkey is the only country to implement 3 of 9 measures before its first case. Discussion and Conclusion: The first encounter dates of countries with the pandemic are important in terms of preparedness. Despite, late-onset countries benefited from the experiences of early-onset countries and implemented measures, the emergence of cases and deaths could not be prevented. Moreover, the increase in cases and deaths was faster. Countries which have more elderly population are affected more adversely. Because the transmission patterns of the pandemic are related with country-specific characteristics, all variables that have an impact on the pandemic should be considered.

ÖzetCOVID-19 pandemisiyle mücadelede ön safta görev yapan sağlık çalışanlarında hastalığa yakalanma riski toplumun birçok kesimine kıyasla daha yüksektir. Risk altındaki bazı grupların zaman zaman taranması vakaların erken dönemde tespiti için önemlidir. Ülkemizde filyasyon, vaka ve temaslı takibi uygulamaları ilçe sağlık müdürlüğü (İlçe SM) ve aile sağlığı merkezi (ASM) çalışanları tarafından yürütülmektedir. Bu çalışmanın amacı, birinci basamak sağlık çalışanlarında COVID-19 görülme sıklığının incelenmesidir. Tanımlayıcı kesitsel türde olan bu araştırmanın evrenini Nisan 2020 itibariyle İstanbul ili Üsküdar ilçesinde görev yapmakta olan 627 birinci basamak sağlık hizmeti çalışanı oluşturmaktadır. 13-30 Nisan 2020 tarihlerinde İlçe SM tarafından yapılan SARS-CoV-2 PCR testi taramasına katılan 586 sağlık çalışanına ait veriler dahil edilerek, tarama dönemine ait nokta prevalans ve Nisan 2020-Nisan 2021 dönemine ait süre prevalans hesaplanmıştır. Katılımcıların yaş ortalaması 38,5±10,3 olup %73,7'si kadındır ve %68,3'ü ASM'de görev yapmaktadır. Tarama sonucuna göre tüm grupta %8,5 olan nokta prevalans; İlçe SM'de %15,1 ve ASM'de %5,5'tir (p<0,001). Süre prevalans ise tüm grupta %25,9 olup İlçe SM'de %34,9 ve ASM'de %21,8'dir (p=0,001). 30.04.2021 itibariyle katılımcıların %17,1'i hiç aşı yaptırmamıştır. ASM çalışanlarına göre daha kalabalık bir ortamda görev yapan İlçe SM çalışanlarında hastalığın daha sık görülmesi hem kurum içi temas ve vaka kümelenmesi açısından dikkatli olunması hem de vakalarla temas edilirken kişisel koruyucu önlemlere üst düzeyde uyulması gerektiğine işaret etmektedir. Aşı uygulamasının başlangıcından 3,5 ay geçmesine rağmen aşı yaptırmayan sağlık çalışanlarının azımsanmayacak düzeyde olması dikkat çekicidir.

Objective: In this study, it was aimed to determine the effects of lockdown due to COVID-19 on the metabolic control in people with type 2 diabetes mellitus. Methods: This cross-sectional study (Ecological trend study) was conducted based on the medical records of patients with type 2 diabetes between September 20, 2019 and September 20, 2020. The metabolic control changes were evaluated as differences of haemoglobin A1c (HbA1c), fasting plasma glucose (FPG), creatinine (Cr), fasting triglyceride (FTG) and low-density lipoprotein-cholesterol (LDL-C) values during pre-lockdown and lockdown periods. The stratified analysis based on age (due to partial closure measures applied over the age of 65) and gender was also performed. Results: There are statistically significant increases between FPG levels and FTG levels in the “during lockdown” group compared to the “pre-lockdown” group (p=0.036 and p=0.013 respectively) while the differences between HbA1c, LDL, cholesterol and creatinine levels are not significant. In subgroup analysis, increases in FPG and FTG levels remained in both