Management Of Infectious Disease Outbreaks Research Articles

Harnessing Artificial Intelligence for Early Detection and Management of Infectious Disease Outbreaks

Infectious diseases pose ongoing threats to global public health, demanding advanced detection methods for effective outbreak management. This study explores integrating artificial intelligence (AI) for early detection and management. AI algorithms analyze diverse datasets, including electronic health records and social media, to identify potential outbreaks. Machine learning models predict disease spread and severity, aiding proactive resource allocation. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses AI's role in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study also evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. Ethical considerations are crucial, emphasizing collaboration between public health agencies, healthcare providers, and technology experts. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. This paper advocates for AI integration to enhance infectious disease surveillance, offering a proactive response to safeguard public health.

Epidemiological cluster identification using multiple data sources: an approach using logistic regression.

In the management of infectious disease outbreaks, grouping cases into clusters and understanding their underlying epidemiology are fundamental tasks. In genomic epidemiology, clusters are typically identified either using pathogen sequences alone or with sequences in combination with epidemiological data such as location and time of collection. However, it may not be feasible to culture and sequence all pathogen isolates, so sequence data may not be available for all cases. This presents challenges for identifying clusters and understanding epidemiology, because these cases may be important for transmission. Demographic, clinical and location data are likely to be available for unsequenced cases, and comprise partial information about their clustering. Here, we use statistical modelling to assign unsequenced cases to clusters already identified by genomic methods, assuming that a more direct method of linking individuals, such as contact tracing, is not available. We build our model on pairwise similarity between cases to predict whether cases cluster together, in contrast to using individual case data to predict the cases' clusters. We then develop methods that allow us to determine whether a pair of unsequenced cases are likely to cluster together, to group them into their most probable clusters, to identify which are most likely to be members of a specific (known) cluster, and to estimate the true size of a known cluster given a set of unsequenced cases. We apply our method to tuberculosis data from Valencia, Spain. Among other applications, we find that clustering can be predicted successfully using spatial distance between cases and whether nationality is the same. We can identify the correct cluster for an unsequenced case, among 38 possible clusters, with an accuracy of approximately 35 %, higher than both direct multinomial regression (17 %) and random selection (< 5 %).

Infectious Diseases Associated with Hydrometeorological Hazards in Europe: Disaster Risk Reduction in the Context of the Climate Crisis and the Ongoing COVID-19 Pandemic.

Hydrometeorological hazards comprise a wide range of events, mainly floods, storms, droughts, and temperature extremes. Floods account for the majority of the related disasters in both developed and developing countries. Flooding alters the natural balance of the environment and frequently establish a favorable habitat for pathogens and vectors to thrive. Diseases caused by pathogens that require vehicle transmission from host to host (waterborne) or a host/vector as part of their life cycle (vector-borne) are those most likely to be affected by flooding. Considering the most notable recent destructive floods events of July 2021 that affected several Central Europe countries, we conducted a systematic literature review in order to identify documented sporadic cases and outbreaks of infectious diseases in humans in Europe, where hydrometeorological hazards, mainly floods, were thought to have been involved. The occurrence of water-, rodent-, and vector-borne diseases in several European countries is highlighted, as flooding and the harsh post-flood conditions favor their emergence and transmission. In this context, strategies for prevention and management of infectious disease outbreaks in flood-prone and flood-affected areas are also proposed and comprise pre- and post-flood prevention measures, pre- and post-outbreak prevention measures, as well as mitigation actions when an infectious disease outbreak finally occurs. Emphasis is also placed on the collision of floods, flood-related infectious disease outbreaks, and the evolving COVID-19 pandemic, which may result in unprecedented multi-hazard conditions and requires a multi-hazard approach for the effective disaster management and risk reduction.

Civil–military cooperation in the management of infectious disease outbreaks: a scoping review

IntroductionCivil–military cooperation (CMC) in infectious disease outbreak responses has become more common, and has its own cooperation dynamics. These collaborations fit WHO’s call for multisectoral cooperation in managing health emergencies...

COVID-19 pandemic in shelters for asylum seekers: a scoping review of preventive measures

ObjectiveTo investigate which measures are recommended by guidelines on prevention and management of infectious disease outbreaks in refugee shelters, how outbreaks have been dealt with in these facilities in the...

Patient and public engagement in decision-making regarding infectious disease outbreak management: an integrative review

IntroductionWorldwide, people experience the effects of infectious disease outbreaks on a regular basis. These effects vary from direct impact of the virus on health, to indirect impact of control measures...

Wildlife-borne microorganisms and strategies to prevent and control emerging infectious diseases

China is one of the countries with the richest wildlife population. The large variety of widely distributed species act as natural or susceptible hosts for numerous infectious diseases. It is estimated that there are more than 1.2 million unknown virus species in China, and there might be 10,000–30,000 unknown bacteria in wild mammals on the Qinghai-Tibet Plateau alone. There are no less than 600,000 species of animal-borne parasites and approximately 2 million species of fungi worldwide. With rapid economic growth and globalization, humans and wildlife interact more frequently, which enhances the probability of wildlife-borne pathogens infecting humans. The occurrence of animal-borne infectious diseases will become the “new normal” we have to face in the future. Therefore, research should be carried out on wildlife-borne microorganisms and the prevention and control of emerging infectious diseases to establish an analytical framework and an evaluation technology system for risk assessment and early warning of potential animal-borne emerging infectious diseases. This will not only improve our understanding of wildlife-borne microbial communities but also enable in-depth analysis, discovery, early warning, and even prediction of major animal-borne emerging infectious diseases that might occur in the future. Furthermore, this research will reduce response times, minimize the social and economic impact and losses, enable interventions related to the emergence or spread of the disease as early as possible, and comprehensively improve our management of infectious disease outbreaks.

Inferring within-flock transmission dynamics of highly pathogenic avian influenza H5N8 virus in France, 2020.

Following the emergence of highly pathogenic avian influenza (H5N8) in France in early December 2020, we used duck mortality data from the index farm to investigate within‐flock transmission dynamics. A stochastic epidemic model was fitted to the daily mortality data and model parameters were estimated using an approximate Bayesian computation sequential Monte Carlo (ABC‐SMC) algorithm. The model predicted that the first bird in the flock was infected 5 days (95% credible interval, CI: 3–6) prior to the day of suspicion and that the transmission rate was 4.1 new infections per day (95% CI: 2.8–5.8). On average, ducks became infectious 4.1 h (95% CI: 0.7–9.1) after infection and remained infectious for 4.3 days (95% CI: 2.8–5.7). The model also predicted that 34% (50% prediction interval: 8%–76%) of birds would already be infectious by the day of suspicion, emphasizing the substantial latent threat this virus could pose to other poultry farms and to neighbouring wild birds. This study illustrates how mechanistic models can help provide rapid relevant insights that contribute to the management of infectious disease outbreaks of farmed animals. These methods can be applied to future outbreaks and the resulting parameter estimates made available to veterinary services within a few hours.

Exploring collective health security in a new age of pandemics. A review of Sara E. Davies’ Containing Contagion.

In Chapter Two, Davies walks the reader through the political context of Southeast Asia in relation to the management of infectious disease outbreaks In Chapter Five, Davies impressively surveys surveillance reports relating to the ASEAN states from 1996 to 2010, thereby tracking the changing performance in disease surveillance and response during this period In Chapter One, Davies provides a historical account of the negotiation and adoption in 2005 of the revised International Health Regulations (IHR), described as "a significant diplomatic coup for the WHO" (p 16) [Extracted from the article] Copyright of Singapore Journal of Tropical Geography is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission However, users may print, download, or email articles for individual use This abstract may be abridged No warranty is given about the accuracy of the copy Users should refer to the original published version of the material for the full abstract (Copyright applies to all Abstracts )

Mental health services for infectious disease outbreaks including COVID-19: a rapid systematic review.

The upsurge in the number of people affected by the COVID-19 is likely to lead to increased rates of emotional trauma and mental illnesses. This article systematically reviewed the available data on the benefits of interventions to reduce adverse mental health sequelae of infectious disease outbreaks, and to offer guidance for mental health service responses to infectious disease pandemic. PubMed, Web of Science, Embase, PsycINFO, WHO Global Research Database on infectious disease, and the preprint server medRxiv were searched. Of 4278 reports identified, 32 were included in this review. Most articles of psychological interventions were implemented to address the impact of COVID-19 pandemic, followed by Ebola, SARS, and MERS for multiple vulnerable populations. Increasing mental health literacy of the public is vital to prevent the mental health crisis under the COVID-19 pandemic. Group-based cognitive behavioral therapy, psychological first aid, community-based psychosocial arts program, and other culturally adapted interventions were reported as being effective against the mental health impacts of COVID-19, Ebola, and SARS. Culturally-adapted, cost-effective, and accessible strategies integrated into the public health emergency response and established medical systems at the local and national levels are likely to be an effective option to enhance mental health response capacity for the current and for future infectious disease outbreaks. Tele-mental healthcare services were key central components of stepped care for both infectious disease outbreak management and routine support; however, the usefulness and limitations of remote health delivery should also be recognized.

Effectiveness of contact tracing and quarantine on reducing COVID-19 transmission: a retrospective cohort study

ObjectivesContact tracing and quarantine are common measures used in the management of infectious disease outbreaks. However, few studies have measured their impact on the control of the COVID-19 pandemic. This study aimed to assess the effectiveness of those measures on reducing transmission of severe acute respiratory syndrome coronavirus 2 in a community setting. Study designThe study design is a retrospective cohort study. MethodsA retrospective cohort study of COVID-19 cases notified in Eastern Porto from March 1st to April 30th, 2020 was performed. Intervention and control cohorts were defined based on whether cases were subjected to contact tracing and quarantine measures before the laboratory confirmation of disease. The number of secondary cases per index case and the proportion of cases with subsequent secondary cases were the primary outcomes. Secondary outcomes included the time from symptom onset to specimen collection and the number of close contacts. The analysis was stratified according to whether national lockdown measures had already been implemented. ResultsThe intervention and control cohorts comprised 98 and 453 cases, respectively. No differences were observed concerning primary outcomes. The intervention group had a shorter time between symptom onset and specimen collection (median: 3 days, interquartile range [IQR]: 1–6, vs. median: 5 days, IQR: 2–7, P-value = 0.004) and fewer close contacts (median: 0, IQR: 0–2, vs. median: 2, IQR: 1–4, P-value<0.001). The stratified analysis returned similar results. ConclusionLocal public health measures were effective in reducing the time between symptom onset and laboratory diagnosis and the number of close contacts per case. No effect was apparent on secondary case figures, suggesting that further measures may be required.

The diagnostic potential of microneedles in infectious diseases

&lt;img src=” https://s3.amazonaws.com/production.scholastica/article/13658/large/prnano_502020_ga.jpg?1594060131”&gt; The coronavirus disease 2019 (COVID-19) pandemic has taught us much about our weaknesses in the management of infectious disease outbreaks. A key lesson has been the need for more effective point-of-care diagnostic tools that not only produce rapid and reliable results, but also facilitate decentralised testing to avoid overwhelming central test facilities when demand peaks in an outbreak. Microneedle devices can be inserted painlessly into the skin to detect biomolecules in the epidermal and dermal layers. They have been used to detect biomarkers both in the interstitial fluid and the capillary blood. Importantly, they are amenable to self-administration. In this article, we provide an overview of existing microneedle-based diagnostic technologies and discuss how they may be built upon to provide effective diagnostic tools for infectious diseases in general.

Evaluating the Preparedness of Child Health Facilities and Health Care Providers to COVID 19 Pandemic

The challenges of diagnosis of SARS-CoV2 infection in the paediatric population includes not only the mild nature of the disease, but the similarity in the symptomatology of the COVID-19 disease to common childhood illness, and the possibility that the infected children could be “silent transmitters” to the family members and health care workers [HCW]. The challenge raises the doubt on the level of preparedness, awareness of the child health facilities [HCF], and HCW in adopting measures at combatting the Coronavirus disease 2019 (COVID-19) pandemic. This study evaluated the preparedness and response of HCF and HCW in paediatric settings to the 2019-novel coronavirus pandemic. A cross-sectional study involving child HCF and HCW. An online tool was used to evaluate preparedness for the management of infectious disease outbreaks as typified by the COVID-19 Outbreak. The information collected included demographic characteristics of the health personnel providing care for children, infection control practices, knowledge, and preparedness for prevention of COVID-19. Data generated were analyzed using the SPSS version 23.0. A majority of respondents were medical doctors (89%), practicing for >5years (75%), and in public health care facilities (69%). A significant proportion of the health facilities had an infectious disease unit (68%) and policy on disease outbreak (60%) in place. 144 (96%) respondents knew SARS-CoV-2 was responsible for COVID-19 and the incubation period was an average of 2 – 14 days. Most of the respondents were aware that the disease could be with or without symptoms (86%), as well as mimic other childhood illnesses (93%). Most of the centres (55%) had fair policy strength towards combating the disease. IPC policies have been established in most paediatric facilities to combat the recurring threat of communicable disease outbreaks. There is a need for further scaling up of resources to address the COVID-19 pandemic.

The application of humane slaughterhouse practices to large-scale culling

Mass culling is a strategy used inthe management of infectious disease outbreaks. The risk of disease spread due to animal transportation often precludes the use of slaughterhouses for this purpose, though they have been used on occasion. Consequently, culling takes place in the less-than-standardised environment on the farm. Regardless of where the cull occurs, the methods chosen to handle and kill the animals must preserve their welfare. This paper attempts to apply the best welfare practices from the controlled environment of the slaughterhouse to the mass culling of ruminants, pigs and poultry. It investigates the key welfare challenges and identifies astute planning executed by competent personnel as a crucial success factor. The urgency; capacity; species, type and age of the animal; personnel; and availability of equipment determine the restraint and killing methods used. The use of good on-farm restraining facilities and mobile killing devices can reasonably be expected to maintain welfare standards for ruminants and poultry. The pig's anatomy, natural behaviour, wide age range and housing types present additional challenges. Objective monitoring throughout the operation is vital for implementing immediate corrective measures whilst also informing procedural reviews. The authors suggest a monitoring tool based on a system currently used in abattoirs, but its limitations must first be validated.

School nurses on frontline in response to measles outbreak

Many school nursing teams in areas affected by the recent measles outbreaks have had to respond quickly. Some of these examples of good practice show the important role they can play in the prevention and management of infectious disease outbreaks.

Pandemic response in low-resource settings requires effective syndromic surveillance

Starbuck et al. have identified a significant gap in any future global response to a severe influenza pandemic.1 The threat of inadequate preparedness and limited public health responses in low-resource settings, leading to uncontrolled transmission is a real and unwelcome possibility during a pandemic. The authors recommend that detailed authoritative guidance should be developed for low-resource settings and that support should be given to governments in these settings to adapt and implement these guidelines. However, an appropriate public health response and effective management of cases depend primarily on early detection of suspected cases. This remains a major challenge in many developing countries, but syndromic surveillance offers a potential solution in these settings. A novel and visionary system, using a simple but standardised set of symptoms, was first developed by T. Jacob John in the early 1980s in Southern India.2 The system utilised a district-level disease surveillance system in a low-resource setting, to control and limit disease outbreaks through early detection. This approach was further adapted in a rural African setting with a focus on rural hospitals reporting presentations of nine core clinical syndromes, including cholera and meningitis-like disease to ensure early identification of infectious disease outbreaks.3 A similar syndromic surveillance system for outbreak detection and response has recently been implemented in Pacific Island Countries and Territories (PICTs). In 2010, PICTS agreed to develop a regional standardised, simple and sustainable event-based syndromic surveillance system to ensure compliance with IHR requirements (rapid outbreak detection, information sharing and response to outbreaks).3 Health resources vary across the region that includes a number of countries that are categorised as least developed countries (LDC). The system is based on the early detection and reporting of four core syndromes (influenza-like illness, diarrhoea, prolonged fever and acute fever with rash) and the immediate reporting of unusual events. The system uses standardised case definitions and processes rather than focussing on a technology platform used to collect or analyse the data. A Pacific Outbreak Manual has been developed as an integral component of the system; to ensure that health workers have rapid access to robust and practical guidelines on the clinical and public health management of infectious disease outbreaks, including influenza-like illness, and triggers for action.4 This provides PICTs with authoritative guidance on appropriate response measures during a severe influenza pandemic. A recent evaluation highlighted the need for standardised surveillance to help meet IHR obligations and to ensure early warning of infectious disease outbreaks across the Pacific.5 While there is variation in system implementation, it is apparent that this is a strength in a region that includes low-resource communities. Despite differences in personnel resources, medical informatics systems and processes, PICTs have productively participated in and contributed to a regional early warning system. The syndromic surveillance system expanded from six to twenty participating PICTs within 1 year, indicating a high level of acceptance of the system. While there are remaining challenges in ensuring uniform data quality, the system has proven effective in detecting outbreaks, its simplicity and the standardisation of both case definitions and responses are key elements in its usefulness. Detection of future influenza pandemics or other emerging infectious disease outbreaks in the South Pacific should be greatly assisted by this syndromic surveillance system. Syndromic surveillance is particularly useful in settings where access to laboratory diagnosis is not timely, allowing containment measures to be implemented prior to having a definitive diagnosis. However, there are inherent limitations in a system based purely on syndromes due to the broad range of diseases that may cause certain syndromes, including influenza-like illness. To avoid exhausting public health resources on ‘syndrome noise’, it is important to select syndromes carefully for their relative public health importance and to establish local thresholds for response. It is important to reach prior agreement on the number of specimens that need to be sent from a particular area for laboratory confirmation at reference laboratories, to allow syndromic surveillance to serve as an efficient early warning system for a severe influenza pandemic. Simplified syndromic surveillance should be a priority in countries with limited public health system or technological capacity.