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Background: Somali Red Crescent Society (SRCS), supported by Norwegian Red Cross, has implemented community-based surveillance (CBS) in Somaliland. This methodology aims to reduce the high risk of epidemics by strengthening early warning and response from and at community level, particularly where there is a weak public health surveillance system. CBS is implemented through SRCS community volunteers, who report signals from the community via SMS to the software platform Nyss. This paper presents key findings from the CBS programme evaluation., Methods: A retrospective observational mixed-methods approach to evaluate the CBS programme was conducted, using routine CBS data from 2021 for Awdal and Togdheer regions and qualitative interviews with stakeholders' representatives., Results: The usefulness of the CBS programme in preventing, detecting, and responding to disease outbreaks was acknowledged by the stakeholders' representatives. 83% of the signals in Awdal region matched a Community Case Definition (CCD) and were escalated to the Ministry of Health and Development (MoHD)). For Togdheer region, 97% were escalated. Verification of signals by supervisors and escalation to the authorities was done timely.Alert outcome and response action was not well recorded, therefore there is limited evidence on sensitivity. The programme was shown to be simple and can be flexibly adjusted for new diseases and changing CCDs.Stakeholders appreciated being engaged, the good collaboration, their participation throughout the implementation and expressed high acceptance of the programme., Conclusion: CBS can support early warning and response for a variety of public health risks. Improved documentation for alert outcomes could help to better evaluate the sensitivity of CBS. A participatory approach is vital to achieve successful community volunteer engagement. Software tools, such as the Nyss platform, can be useful to support effective and efficient CBS implementation., (© 2024. The Author(s).)

Background: The resources available to fight an epidemic are typically limited, and the time and effort required to control it grow as the start date of the containment effort are delayed. When the population is afflicted in various regions, scheduling a fair and acceptable distribution of limited available resources stored in multiple emergency resource centers to each epidemic area has become a serious problem that requires immediate resolution., Methods: This study presents an emergency medical logistics model for rapid response to public health emergencies. The proposed methodology consists of two recursive mechanisms: (1) time-varying forecasting of medical resources and (2) emergency medical resource allocation. Considering the epidemic's features and the heterogeneity of existing medical treatment capabilities in different epidemic areas, we provide the modified susceptible-exposed-infected-recovered (SEIR) model to predict the early stage emergency medical resource demand for epidemics. Then we define emergency indicators for each epidemic area based on this. By maximizing the weighted demand satisfaction rate and minimizing the total vehicle travel distance, we develop a bi-objective optimization model to determine the optimal medical resource allocation plan., Results: Decision-makers should assign appropriate values to parameters at various stages of the emergency process based on the actual situation, to ensure that the results obtained are feasible and effective. It is necessary to set up an appropriate number of supply points in the epidemic emergency medical logistics supply to effectively reduce rescue costs and improve the level of emergency services., Conclusions: Overall, this work provides managerial insights to improve decisions made on medical distribution as per demand forecasting for quick response to public health emergencies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Hu, Jiang, Yao, Chen, Yue, Zhao and Wen.)

The COVID-19 pandemic provides a once-in-a-lifetime opportunity to learn more about how businesses are affected by and adapt to large-scale, unforeseen shocks. Our research examines the worries of a sample of Italian publicly traded companies about the spread of COVID-19. The information was gathered from a dataset employing text-based estimates of the main concerns listed companies have about the development of COVID-19 and other pandemic diseases. These data can be used to determine whether companies stand to earn or lose money because of a particular outbreak. We concentrate on the data for Italy, which allows us to quantify which of the sample's Italian enterprises are more exposed and thus affected, the severity of risk perception, and the firm's attitude towards​ the shock exposure. We attempt to explain how firm perceptions of the COVID-19 crisis are correlated with various types of indicators related to economic and financial status, such as financial position (total debt exposure and short-term exposure), ROI, and ROE during the COVID-19 crisis, i.e. the main firms' responses to such a large shock., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 Economic Society of Australia, Queensland. Published by Elsevier B.V. All rights reserved.)

Epidemic diseases (EDs) present a significant but challenging risk endangering public health, evidenced by the outbreak of COVID-19. Compared to other risks affecting public health such as flooding, EDs attract little attention in terms of risk assessment in the current literature. It does not well respond to the high practical demand for advanced techniques capable of tackling ED risks. To bridge this gap, an adapted fuzzy evidence reasoning method is proposed to realize the quantitative analysis of ED outbreak risk assessment (EDRA) with high uncertainty in risk data. The novelty of this article lies in (1) taking the lead to establish the outbreak risk evaluation system of epidemics covering the whole epidemic developing process, (2) combining quantitative and qualitative analysis in the fields of epidemic risk evaluation, (3) collecting substantial first-hand data by reviewing transaction data and interviewing the frontier experts and policymakers from Chinese Centers for Disease Control and Chinese National Medical Products Administration. This work provides useful insights for the regulatory bodies to (1) understand the risk levels of different EDs in a quantitative manner and (2) the sensitivity of different EDs to the identified risk factors for their effective control. For instance, in the case study, we use real data to disclose that influenza has the highest breakout risk level in Beijing. The proposed method also provides a potential tool for evaluating the outbreak risk of COVID-19., (© 2021 Society for Risk Analysis.)

Telemedicine was originally created as a way to treat patients who were located in remote places far away from local health facilities or in areas with shortages of medical professionals. Telemedicine is still used today to address those problems, and is increasingly becoming a tool for convenient medical care. With the emergence of pandemics, telemedicine became almost a mandatory and valuable option for continuing to provide medical care in various specialties. As the threat of pandemic progress has continued for months and may continue for years, it is essential to validate existing tools to maintain clinical assessment and patient treatment to avoid negative consequences of the lack of medical follow-up. Therefore, the establishment of a virtual assessment technique that can be conducted effectively is of outmost importance as a way of adapting to the current situation. This study evaluated the role of telemedicine in the assessment of various orthopedic pathologies by means of a systematic virtual evaluation., Competing Interests: Conflict-of-interest statement: The authors declare that they have no conflicting interests., (©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.)

Existing compartmental models in epidemiology are limited in terms of optimizing the resource allocation to control an epidemic outbreak under disease growth uncertainty. In this study, we address this core limitation by presenting a multi-stage stochastic programming compartmental model, which integrates the uncertain disease progression and resource allocation to control an infectious disease outbreak. The proposed multi-stage stochastic program involves various disease growth scenarios and optimizes the distribution of treatment centers and resources while minimizing the total expected number of new infections and funerals. We define two new equity metrics, namely infection and capacity equity, and explicitly consider equity for allocating treatment funds and facilities over multiple time stages. We also study the multi-stage value of the stochastic solution (VSS), which demonstrates the superiority of the proposed stochastic programming model over its deterministic counterpart. We apply the proposed formulation to control the Ebola Virus Disease (EVD) in Guinea, Sierra Leone, and Liberia of West Africa to determine the optimal and fair resource-allocation strategies. Our model balances the proportion of infections over all regions, even without including the infection equity or prevalence equity constraints. Model results also show that allocating treatment resources proportional to population is sub-optimal, and enforcing such a resource allocation policy might adversely impact the total number of infections and deaths, and thus resulting in a high cost that we have to pay for the fairness. Our multi-stage stochastic epidemic-logistics model is practical and can be adapted to control other infectious diseases in meta-populations and dynamically evolving situations., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.)

At the end of 2019, the world faced the novel coronavirus, and with it fear of economic collapse and mass fatalities. Simulation systems can be used to monitor the behavior of the virus. Simulation provides an abstract representation of reality by conveying details and characteristics of reality in a simple application. One of the most important ways to simulate is agent-based modeling. The health information professional plays an important role in developing these models. In this research, we simulate the spread of COVID-19 in a region restricted to a population with specific demographic characteristics and social relationships. This study aims to clarify the effects of preventative techniques that suppress the spread of epidemics, such as quarantines, social distancing, and reduced mass transit., (Copyright © 2021 by the American Health Information Management Association.)

The rapid spread of COVID-19 motivated countries worldwide to mitigate mortality through actions including social distancing, home quarantine, school closures, and case isolation. We estimate the global mortality benefits of these actions. We use county-level data on COVID-19 from January 2020, project the number of mortalities until September 2020, and calculate the global mortality benefits using the age- and country-specific value of a statistical life (VSL). Implementing all four types of actions above would save approximately 40.76 trillion USD globally, with social distancing accounting for 55% of the benefits. The monetary benefit would be the largest in the US, Japan and China. Our findings indicate that global actions during COVID-19 have substantial economic benefits and must be implemented in response to COVID-19., (© 2020 Elsevier Inc. All rights reserved.)

Like soldiers, frontline medical staff provide a first line of defense and have played a critical role in responses to the outbreak of coronavirus disease-2019 in December 2019. It is important to acknowledge the considerable pressure placed on frontline medical staff in the face of a new type of coronavirus that is highly infectious and for which no specific treatment is available. Here, we review the various kinds of psychological problems afflicting frontline medical staff who are combatting the severe acute respiratory syndrome epidemic. These include anxiety, insomnia, depression, interpersonal difficulties, and post-traumatic stress disorder syndrome. We further present a summary of countermeasures for alleviating these problems based on our findings. These countermeasures include ensuring the provision of adequate protective gear for frontline medical staff, developing timely and clear guidelines, strengthening social support, and providing clear criteria and additional training, focusing on the choice of frontline medical staff. An understanding of the psychological impacts of an epidemic situation and of relevant countermeasures will contribute to reducing the psychological pressures on frontline medical staff. Consequently, they will be able to cope better with outbreaks of infectious diseases in the future, to reduce the psychological pressure of the front-line medical staff, and to improve the treatment level., Competing Interests: Conflict-of-interest statement: The authors report no conflicts of interest in this work., (©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.)

The name of Karol Kaczkowski, one of the pioneers of Polish epidemiology of the 19th century, has been somewhat forgotten. Hence, it is worth getting acquainted with his actions that he made contributing to the effective inhibition of the spread of the cholera epidemic that hit Polish territory in the 1830s. KAROL KACZKOWSKI (1797-1867) General of Staff of the Polish Army, doctor, professor, He was born in Warsaw on 2 February 1797. In 1805 his parents moved to Krzemieniec. In 1815, he began medical studies at the University of Vilnius. He was friends with philomaths: Adam Mickiewicz and Tomasz Zan. In 1821 he obtained the degree of doctor of medicine. In the years 1824-1828 he traveled around Europe. In 1829, he was nominated the Head of the Therapeutic Clinic at the University of Warsaw. After the outbreak of the November Uprising on November 29, 1830, he joined the artillery and in 1831 was appointed chief physician of the Polish Army. He organized the command of the military health service, hospitals and field hospitals. After the battle of Grochów, he organized battalion dressing points and a cordon of doctors who provided quick help to the wounded. On February 5, 1831, Karol Kaczkowski was appointed the Chief Physician of the Polish Army. When the first cholera patients, brought in by the Russian army, arrived in Warsaw in the spring of 1831, he prepared instructions on how to detect and treat cholera. He created cholera hospitals in Mienia and Warsaw, and sanitary supervision in military units. For this he was awarded the Wirtuti Militari Gold Cross. After the fall of the uprising, he left Poland with a group of 2,000. injured. He got to Prussia, and then to Lviv. In 1854 he settled in Żytomierz. He suffered harassment from the tsarist authorities. In 1863, during the January Uprising, he was sent to the Voronezh Governorate. In 1867, he obtained a permit to travel to Kherson, where he died on September 14, 1867., (© National Institute of Public Health – National Institute of Hygiene.)

Urban green space has been proven effective in improving public health in the contemporary background of planetary urbanization. There is a growing body of literature investigating the relationship between non-communicable diseases (NCDs) and green space, whereas seldom has the correlation been explored between green space and epidemics, such as dysentery, tuberculosis, and malaria, which still threaten the worldwide situation of public health. Meanwhile, most studies explored healthy issues with the general green space, public green space, and green space coverage, respectively, among which the different relevance has been rarely explored. This study aimed to examine and compare the relevance between these three kinds of green space and incidences of the three types of epidemic diseases based on the Panel Data Model (PDM) with the time series data of 31 Chinese provinces from 2007 to 2016. The results indicated that there exists different, or even opposite, relevance between various kinds of green space and epidemic diseases, which might be associated with the process of urban sprawl in rapid urbanization in China. This paper provides a reference for re-thinking the indices of green space in building healthier and greener cities.

The CRISPR-Cas system is a key technology for genome editing and regulation in a wide range of organisms and cell types. Recently, CRISPR-Cas-based diagnostic platform has shown idealistic properties for pathogen detection. Integrating the CRISPR-Cas platform along with lateral flow system allows rapid, sensitive, specific, cheap, and reliable diagnostic. It has the potential to be in frontline for not only pathogen detection during the epidemic outbreak, but also cancer, and genetic diseases., (© 2018 Wiley Periodicals, Inc.)