In the past, Vietnam was impacted by numerous epidemics, particularly during the Nguyễn Dynasty from 1802 to 1883. Based on data from the Đại Nam Thực Lục (1961) (The Veritable Records of the Great South), this article investigates the frequency and nature of these epidemics, identifies the types of common diseases at that time, and explores the underlying causes of these outbreaks. The study further examines the Nguyễn Dynasty's strategies for managing these health crises. During these outbreaks, the dynasty faced significant challenges, with frequent epidemics leading to high death rates, widespread social disruption, and economic decline. The dynasty's primary preventive measures, heavily reliant on spiritual practices like prayer, highlight the limited medical understanding at the time and the constraints of its socio-political framework. However, there was a progressive shift towards the incorporation of Western medical innovations, particularly in the vaccine approach to treat diseases like smallpox. This transition not only marked a critical evolution in the local healthcare approach but also set the stage for more systematic medical advancements in Vietnam during the colonial period (1884–1945).

This paper retrospectively analysed the prevalence of macrolide-resistant Mycoplasma pneumoniae (MRMP) in some parts of China. Between January 2013 and December 2019, we collected 4,145 respiratory samples, including pharyngeal swabs and alveolar lavage fluid. The highest PCR-positive rate of M. pneumoniae was 74.5% in Beijing, the highest resistance rate was 100% in Shanghai, and Gansu was the lowest with 20%. The highest PCR-positive rate of M. pneumoniae was 74.5% in 2013, and the highest MRMP was 97.4% in 2019; the PCR-positive rate of M. pneumoniae for adults in Beijing was 17.9% and the MRMP was 10.48%. Among the children diagnosed with community-acquired pneumonia (CAP), the PCR-positive and macrolide-resistant rates of M. pneumoniae were both higher in the severe ones. A2063G in domain V of 23S rRNA was the major macrolide-resistant mutation, accounting for more than 90%. The MIC values of all MRMP to erythromycin and azithromycin were ≥ 64 μg/ml, and the MICs of tetracycline and levofloxacin were ≤ 0.5 μg/ml and ≤ 1 μg/ml, respectively. The macrolide resistance varied in different regions and years. Among inpatients, the macrolide-resistant rate was higher in severe pneumonia. A2063G was the common mutation, and we found no resistance to tetracycline and levofloxacin.

With recent epidemics such as COVID-19, H1N1 and SARS causing devastating financial loss to the economy, it is important that insurance companies plan for financial costs of epidemics. This article proposes a new methodology for epidemic and insurance modelling by combining the existing deterministic compartmental models and the Markov multiple state models to facilitate actuarial computations to design new health insurance plans that cover epidemics. Our method is inspired by the seminal paper (Feng and Garrido (2011) North American Actuarial Journal, 15, 112–136.) of Feng and Garrido and complements the work of Hillairet and Lopez et al. in Hillairet and Lopez ((2021) Scandinavian Actuarial Journal, 2021(8), 671–694.) and Hillairet et al. ((2022) Insurance: Mathematics and Economics, 107, 88–101.) In this work, we use the deterministic SIR model and the Eyam epidemic data set to provide numerical illustrations for our method.

Understanding the relationship between infectious disease outbreaks and natural disasters is important in developing response and disaster risk reduction strategies. The aim of this study was to identify outbreaks associated with natural disasters during the past 20 y, and outline risk factors and mechanisms for postdisaster outbreaks. Review of the international disaster database (EM-DAT) and systematic review of the literature were conducted. The records of disaster events in EM-DAT during the past 20 y were screened. A literature search was carried out in the databases PubMed and Embase. Articles in English language published between 2000 and 2020 were searched. Data were extracted from articles and Narrative synthesis was used to summarize the findings. We found 108 events associated with epidemics, the majority being floods. We found 36 articles, most of them focused on outbreaks after floods. Risk factors and mechanisms that contributed to the outbreaks were mainly related to the consequences of disaster and its impact on the environment and living conditions of population. Infrastructure readiness and postdisaster measures play important roles in controlling the spread of epidemics after natural disasters. More evidence and research are required for better understanding of the association between natural disasters and infectious diseases outbreaks.

This article proposes the adoption of a multi-modal system for allocating vaccine doses during large transnational outbreaks of infectious diseases. The chosen allocative criteria (public health need; country-income level; qualification through funding; and, subsidiarily, a modified lottery system) are adapted from a current embodiment of allocative multi-modality outside the context of public health: the New York City Marathon.

The COVID-19 epidemic showed inter-regional differences in Italy. We used an ecological study design and publicly available data to compare the basic reproduction number (R0), the doubling time of the infection (DT) and the COVID-19 cumulative incidence (CI), death rate, case fatality rate (CFR) and time lag to slow down up to a 50-days doubling time in the first and the second 2020 epidemic waves (δDT50) by region. We also explored socio-economic, environmental and lifestyle variables with multiple regression analysis. COVID-19 CI and CFR changed in opposite directions in the second vs. the first wave: the CI increased sixfold with no evidence of a relationship with the testing rate; the CFR decreased in the regions where it was initially higher but increased where it was lower. The R0 did not change; the initially mildly affected regions, but not those where the first wave had most severely hit, showed a greater δDT50 amplitude. Vehicular traffic, average temperature, population density, average income, education and household size showed a correlation with COVID-19 outcomes. The deadly experience in the first epidemic wave and the varying preparedness of the local health systems might have contributed to the inter-regional differences in the second COVID-19 epidemic wave.

The COVID-19 pandemic struck Spain severely from the beginning. Prevention via information that fosters knowledge, reasonable concern, control, and personal care is the most effective means to slow down the pandemic. In this intervention field study, first, we assessed actual knowledge, concern, control, and care about the COVID-19 in 111 Spanish university teachers and students. Subsequently, we randomly assigned them to two groups. One group (n = 53) received uncertain information about prevention measures, whereas the other group (n = 58) received certain information. Analysis of covariance, using baseline measures as covariates, revealed that the group receiving the certain information reported an immediately increased perceived control and personal care about the pandemic. These findings suggest that measures that are known to be effective in COVID-19 prevention, if communicated with certainty (i.e., solid evidence), could influence people's attitudes, possibly through the schematic organisation of new information.

In December 2019, an outbreak of an unknown cause of pneumonia (later named coronavirus disease 2019 [COVID-19]) occurred in Wuhan, China. This was found to be attributed to a novel coronavirus of zoonotic origin, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; previously named 2019 novel coronavirus or 2019-nCoV). The SARS-CoV-2, a new type of highly pathogenic human coronavirus related to severe acute respiratory syndrome coronavirus (SARS-CoV), spread rapidly worldwide and caused 246,303,023 confirmed infections, including 4,994,160 deaths, by October 31, 2021. SARS-CoV-2 and SARS-CoV vary in their specific characteristics, regarding epidemics and pathogenesis. This article focuses on the comparison of the virology, epidemiology, and clinical features of SARS-CoV and SARS-CoV-2 to reveal their common and distinct properties, to provide an up-to-date resource for the development of advanced systems and strategies to monitor and control future epidemics of highly pathogenic human coronaviruses.

The COVID-19 pandemic is a global traumatic experience for citizens, especially during sensitive time windows of heightened plasticity such as pregnancy and neonatal life. Pandemic-related stress experienced by mothers during pregnancy may act as an early risk factor for infants’ regulatory capacity development by altering maternal psychosocial well-being (e.g., increased anxiety, reduced social support) and caregiving environment (e.g., greater parenting stress, impaired mother–infant bonding). The aim of the present longitudinal study was to assess the consequences of pandemic-related prenatal stress on infants’ regulatory capacity. A sample of 163 mother–infant dyads was enrolled at eight maternity units in northern Italy. They provided complete data about prenatal stress, perceived social support, postnatal anxiety symptoms, parenting stress, mother–infant bonding, and infants’ regulatory capacity at 3 months of age. Women who experienced emotional stress and received partial social support during pregnancy reported higher anxious symptoms. Moreover, maternal postnatal anxiety was indirectly linked to the infants’ regulatory capacity at 3 months, mediated by parenting stress and mother–infant bonding. Dedicated preventive interventions should be delivered to mothers and should be focused on protecting the mother–infant dyad from the detrimental effects of pandemic-related stress during the COVID-19 healthcare emergency.