Visual Data Analysis and Simulation Prediction for COVID-19

Bottom-up citizen engagement for health emergency and disaster risk management: directions since COVID-19

On the application of mathematical models of schistosome transmission dynamics. I. Natural transmission

Sub-Saharan Africa harbours the majority of the burden of Lassa fever. Clinical diseases, as well as high seroprevalence, have been documented in Nigeria, Sierra Leone, Liberia, Guinea, Ivory Coast, Ghana, Senegal, Upper Volta, Gambia, and Mali. Deaths from Lassa fever occur all year round but naturally peak during the dry season. Annually, the number of people infected is estimated at 100,000 to 300,000, with approximately 5,000 deaths. There have been some work done on the dynamics of Lassa fever disease transmission, but to the best of our knowledge, none has been able to capture the seasonal variation of Mastomys rodent population and its impact on the transmission dynamics. In this work, a periodically forced seasonal nonautonomous system of a nonlinear ordinary differential equation is developed that captures the dynamics of Lassa fever transmission and seasonal variation in the birth of Mastomys rodents where time was measured in days to capture seasonality. It was shown that the model is epidemiologically meaningful and mathematically well posed by using the results from the qualitative properties of the solution of the model. A time-dependent basic reproduction number RLt is obtained such that its yearly average is written as R˜L<1, when the disease does not invade the population (means that the number of infected humans always decreases in the seasons of transmission), and R˜L>1, when the disease remains constantly and is invading the population, and it was detected that R˜L≠RL. We also performed some evaluation of the Lassa fever disease intervention strategies using the elasticity of the equilibrial prevalence in order to predict the optimal intervention strategies that can be useful in guiding the local national control program on Lassa fever disease to make a proper decision on the intervention packages. Numerical simulations were carried out to illustrate the analytical results, and we found that the numerical simulations of the model showed that possible combined intervention strategies would reduce the spread of the disease. It was established that, to eliminate Lassa fever disease, treatments with ribavirin must be provided early to reduce mortality and other preventive measures like an educational campaign, community hygiene, isolation of infected humans, and culling/destruction of rodents must be applied to also reduce the morbidity of the disease. Finally, the obtained results gave a primary framework for planning and designing cost-effective strategies for good interventions in eliminating Lassa fever.

The Characteristics of Middle Eastern Respiratory Syndrome Coronavirus Transmission Dynamics in South Korea

Behavioral risk factors, such as smoking, excessive alcohol consumption, physical inactivity, obesity, and unhealthy food intake are added risk factors for severe outcomes of COVID-19 infections. Preventive measures to avoid infections are therefore particularly important for individuals engaging in behavioral risk factors. We seek to determine whether behavioral risk factors (BRFs) play a significant role in the adherence to preventive COVID-19 measures in a population aged 50 and above. The SHARE wave 8 (Survey of Health, Ageing and Retirement in Europe) and SHARE COVID-19 Survey served as the database, resulting in an analytical sample of 17,588 respondents from 23 European countries plus Israel. Of these 36.04% engaged in at least one BRF and 16.68% engaged in 3 or more BRFs. Multilevel logistic regressions revealed that engagement in one BRF was significantly associated with less adherence to hygiene preventive measures, i.e., hand-sanitizing, hand-washing and covering coughs and sneezes (OR: 0.86; 95% CI: 0.78; 0.94), as was engagement in two BRFs (OR: 0.85; 95% CI: 0.74; 0.97) and three or more BRFs (OR: 0.72; 95% CI: 0.59; 0.88). No such association was found between engagement in BRFs and adherences to social isolation preventive measures, i.e., avoiding meeting more than five people, visiting others or going shopping, or regulated preventive measures, i.e., wearing a mask and keeping physical distance. The found association was also stronger when three or more BRFs were engaged in (1 vs. 3 BRFs: χ2 = 3.43, p = 0.06; 2 vs. 3 BRFs: χ2 = 6.05; p = 0.01). The study gives insight into the protective behavior of a population with inherent vulnerability during a global health emergency. It lays the foundation for follow-up research about the evolution of adherence to preventive measures as the pandemic progresses and about long-term behavioral changes. In addition, it can aide efforts in increasing preventive compliance by raising awareness of the added risk behavioral risk factors pose.

The Cost-Effectiveness Analysis of a Quadrivalent Human Papillomavirus Vaccine (6/11/16/18) for Females in Japan

This thesis investigates the decision-making processes surrounding the declaration of a Public Health Emergency of International Concern (PHEIC) to unpack the complex interplay of factors underlying this political decision and examine the mechanisms that govern global health emergencies within the framework of the International Health Regulations (IHR). Positioning the PHEIC decision within the WHOs emergency response framework, the study goes beyond the role of the Emergency Committees (EC), delving into the less visible yet critical assessments, criteria, and procedures that inform these decisions, often overshadowed in literature. Additionally, this research considers the global health security paradigm as the main ideational factor guiding the governance of global health emergencies. This thesis analyzes the historical and ideological origins of both the IHR and global health security paradigm, revealing a legacy rooted in colonial-era practices focused on disease containment and the protection of Western interests. This legacy has shaped WHOs bureaucratic culture, where a health security lens permeates daily practices like disease surveillance and risk assessment, and underpins the WHOs expert authority to classify and respond to health risks. The case study of the Ebola outbreak in the Democratic Republic of the Congo (DRC) (2018-2020) highlights the complexities of determining a PHEIC, showing how local political, security, and logistical challenges influence the timing and nature of a PHEIC declaration. The case study also illustrates how the global health security paradigm shapes both the interpretation of the PHEIC criteria within the EC and the global health response on the ground. By expanding the analysis beyond the PHEIC decision itself to include the operational procedures and norms that guide it, this research argues that global health security is operationalized not solely through high-level declarations but also through the everyday practices of surveillance and risk management embedded within the WHOs emergency response framework. By unpacking these mechanisms, this thesis offers new insights into the governance of global health emergencies, illustrating how historical legacies and ideational factors shape what constitutes an event of international concern and inform the WHOs approach to global health crises.

Background and PurposeIn public health emergencies, rapid perception and analysis of public demands are essential prerequisites for effective crisis communication. Public demands serve as the most instinctive response to the current state of a public health crisis. Therefore, the government must promptly grasp and leverage public demands information to enhance the effectiveness and efficiency of health emergency management, that is planned to better deal with the outbreak and meet the medical demands of the public.MethodsThis study employs dynamic topic mining and knowledge graph construction to analyze public demands, presenting a spatial-temporal evolution analysis method for emergencies based on EBU models. EBU models are three large language models, including ERNIE, BERTopic, and UIE.ResultsThe data analysis of Shanghai’s city closure and control during the COVID-19 epidemic has verified that this method can simplify the labeling and training process, and can use massive social media data to quickly, comprehensively, and accurately analyze public demands from both time and space dimensions. From the visual analysis, geographic information on public demands can be quickly obtained and areas with serious problems can be located. The classification of geographical information can help guide the formulation and implementation of government policies at different levels, and provide a basis for health emergency material dispatch.ConclusionThis study extends the scope and depth of research on health emergency management, enriching subject categories and research methods in the context of public health emergencies. The use of social media data underscores its potential as a valuable tool for analyzing public demands. The method can provide rapid decision supports for decision-making for public services such as government departments, centers for disease control, medical emergency centers and transport authorities.

Public health agencies have suggested nonpharmaceutical interventions to curb the spread of the COVID-19 infections. The study intended to explore the information-seeking behavior and information needs on preventive measures for COVID-19 in the Philippine context. The search interests and related queries for COVID-19 terms and each of the preventive measures for the period from December 31, 2019 to April 6, 2020 were generated from Google Trends. The search terms employed for COVID-19 were coronavirus, ncov, covid-19, covid19 and “covid 19.” The search terms of the preventive measures considered for this study included “community quarantine”, “cough etiquette”, “face mask” or facemask, “hand sanitizer”, handwashing or “hand washing” and “social distancing.” Spearman’s correlation was employed between the new daily COVID-19 cases, COVID-19 terms and the different preventive measures. The relative search volume for the coronavirus disease showed an increase up to the pronouncement of the country’s first case of COVID-19. An uptrend was also evident after the country’s first local transmission was confirmed. A strong positive correlation (rs = .788, p < .001) was observed between the new daily cases and search interests for COVID-19. The search interests for the different measures and the new daily cases were also positively correlated. Similarly, the search interests for the different measures and the COVID-19 terms were all positively correlated. The search interests for “face mask” or facemask, “hand sanitizer” and handwashing or “hand washing” were more correlated with the search interest for COVID-19 than with the number of new daily COVID-19 cases. The search interests for “cough etiquette”, “social distancing” and “community quarantine” were more correlated with the number of new daily COVID-19 cases than with the search interest for COVID-19. The public sought for additional details such as type, directions for proper use, and where to purchase as well as do-it-yourself alternatives for personal protective items. Personal protective or community measures were expected to be accompanied with definitions and guidelines as well as be available in translated versions. Google Trends could be a viable option to monitor and address the information needs of the public during a disease outbreak. Capturing and analyzing the search interests of the public could support the design and timely delivery of appropriate information essential to drive preventive measures during a disease outbreak.

COVID-19 disease caused by the novel SARS-CoV-2 coronavirus has already brought unprecedented challenges for public health and resulted in huge numbers of cases and deaths worldwide. In the absence of effective vaccine, different countries have employed various other types of non-pharmaceutical interventions to contain the spread of this disease, including quarantines and lockdowns, tracking, tracing and isolation of infected individuals, and social distancing measures. Effectiveness of these and other measures of disease containment and prevention to a large degree depends on good understanding of disease dynamics, and robust mathematical models play an important role in forecasting its future dynamics. In this paper we focus on Ukraine, one of Europe’s largest countries, and develop a mathematical model of COVID-19 dynamics, using latest data on parameters characterising clinical features of disease. For improved accuracy, our model includes age-stratified disease parameters, as well as age- and location-specific contact matrices to represent contacts. We show that the model is able to provide an accurate short-term forecast for the numbers and age distribution of cases and deaths. We also simulated different lockdown scenarios, and the results suggest that reducing work contacts is more efficient at reducing the disease burden than reducing school contacts, or implementing shielding for people over 60.

In this paper a mathematical model of monkey pox virus transmission dynamics with two interacting host populations; humans and rodents is formulate. The quarantine class and public enlightenment campaign parameter are incorporated into human population as means of controlling the spread of the disease. The Disease Free Equilibrium (DFE) and Endemic Equilibrium (EE) are obtained. The basic reproduction number R 0 h and R 0 r are computed and used for the analysis. The Disease Free Equilibrium (DFE) is analyzed for stability using Jacobian matrix techniques and Lyapunov function. Stability analysis shows that the DFE is stable if R 0 h <1 and R 0 r <1.

In this paper, we present a mathematical model of COVID-19 transmission dynamics and control strategies. The result reveal that the disease free equilibrium point exists and it is locally and globally asymptotically stable when the reproduction number is less than one unit and otherwise unstable when is greater than one unit. Simulation and discussions of a different variable of the model has been performed and we have compute sensitivity index of each parameter through sensitivity analysis of different embedded parameters. MATLAB of ode45 was employed perform numerical simulation analysis and the results show that there is importance of isolating infectious individual in an epidemic disease within the population.

Malaria remains a substantial public health challenge and economic burden globally. Currently, malaria has been declared as endemic in 85 countries. In this study, we developed and analyzed a fractional-order mathematical model for malaria transmission dynamics that incorporates variability of temperature and rainfall using Caputo-type AB operators. The existence and uniqueness of the model's solutions were established using the Banach fixed-point theorem. The model system's equilibria (both disease-free and endemic) were identified, and lemmas and theorems were developed to prove their stability. Furthermore, we used different temperature ranges and rainfall data, validating them against existing literature. Numerical simulations using the Toufik-Atangana schemes with various fractional-order alpha values revealed that as the value of alpha approaches 1, the behavior of the fractional-order model converges to that of the classical model. The numerical results are promising and are expected to be valuable for future research related to fractional-order models.

International audience

Background/Introduction:Health emergencies such as the COVID-19 pandemic strain health systems and emergency response mechanisms. Identifying critical points during the response cycle where emergency workforce and operational capacity can be improved can help break the protracted nature of responses. Global health emergency workforce, or health emergency and alert response teams such as multidisciplinary Public Health Rapid Response Teams (RRTs) and Emergency Medical Teams (EMTs), play critical roles in the response to public health emergencies.Objectives:The project aims to explore and understand how countries manage and operationalize their RRT and EMT programs. With anecdotal evidence of countries integrating the two historically disparate groups, we propose to examine how countries are jointly or separately addressing legal frameworks and policies; management practices; reporting processes and protocols; training; as well as program operations and standards.Method/Description:Through existing global partnerships and networks, a convenience sample of national focal points responsible for the management of their RRT and EMT program are sent an online survey followed by participating in a one-on-one interview. Quantitative and qualitative analyses will be conducted.Results/Outcomes:Twelve countries representing all six World Health Organization regions with both RRT and EMT programs have been selected for engagement.Conclusion:Factors contributing to or against countries integration of RRT and EMT programs will be identified. Areas of divergence or synergy of plans and standard operating procedures will be mapped. Recommendations for strengthening global health emergency alert and response teams will be generated.