Early Response System Research Articles

Harmonizing Multisource Data to Inform Vector-Borne Disease Risk Management Strategies.

In the last few decades, we have witnessed the emergence of new vector-borne diseases (VBDs), the globalization of endemic VBDs, and the urbanization of previously rural VBDs. Data harmonization forms the basis of robust decision-support systems designed to protect at-risk communities from VBD threats. Strong interdisciplinary partnerships, protocols, digital infrastructure, and capacity-building initiatives are essential for facilitating the coproduction of robust multisource data sets. This review provides a foundation for researchers and practitioners embarking on data harmonization efforts to (a) better understand the links among environmental degradation, climate change, socioeconomic inequalities, and VBD risk; (b) conduct risk assessments, health impact attribution, and projection studies; and (c) develop robust early warning and response systems. We draw upon best practices in harmonizing data for two well-studied VBDs, dengue and malaria, and provide recommendations for the evolution of research and digital technology to improve data harmonization for VBD risk management.

Prediction model of in-hospital cardiac arrest using machine learning in the early phase of hospitalization.

In hospitals, the deterioration of a patient's condition leading to death is often preceded by physiological abnormalities in the hours to days beforehand. Several risk-scoring systems have been developed to identify patients at risk of major adverse events; however, such systems often exhibit low sensitivity and specificity. To identify the risk factors associated with in-hospital cardiac arrest (IHCA), we conducted a retrospective cohort study at a tertiary medical center in Taiwan. Four machine learning algorithms were employed to identify the factors most predictive of IHCA. The support vector machine model was discovered to be the most effective at predicting IHCA. The ten most critical physiological parameters at 8 h prior to the event were pulse rate, age, white blood cell count, lymphocyte count, body temperature, body mass index, systolic and diastolic blood pressure, platelet count, and use of central nervous system-active medication. Using these parameters, we can enhance early warning and rapid response systems in our hospital, potentially reducing the incidence of IHCA in clinical practice.

Cardiac Arrest and Cardiopulmonary Resuscitation Outcome Reports: 2024 Update of the Utstein Out-of-Hospital Cardiac Arrest Registry Template.

The Utstein Out-of-Hospital Cardiac Arrest Resuscitation Registry Template, introduced in 1991 and updated in 2004 and 2015, standardizes data collection to enable research, evaluation, and comparisons of systems of care. The impetus for the current update stemmed from significant advances in the field and insights from registry development and regional comparisons. This 2024 update involved representatives of the International Liaison Committee on Resuscitation and used a modified Delphi process. Every 2015 Utstein data element was reviewed for relevance, priority (core or supplemental), and improvement. New variables were proposed and refined. All changes were voted on for inclusion. The 2015 domains-system, dispatch, patient, process, and outcomes-were retained. Further clarity is provided for the definitions of out-of-hospital cardiac arrest attended resuscitation and attempted resuscitation. Changes reflect advancements in dispatch, early response systems, and resuscitation care, as well as the importance of prehospital outcomes. Time intervals such as emergency medical service response time now emphasize precise reporting of the times used. New flowcharts aid the reporting of system effectiveness for patients with an attempted resuscitation and system efficacy for the Utstein comparator group. Recognizing the varying capacities of emergency systems globally, the writing group provided a minimal dataset for settings with developing emergency medical systems. Supplementary variables are considered useful for research purposes. These revisions aim to elevate data collection and reporting transparency by registries and researchers and to advance international comparisons and collaborations. The overarching objective remains the improvement of outcomes for patients with out-of-hospital cardiac arrest.

Cardiac arrest and cardiopulmonary resuscitation outcome reports: 2024 update of the Utstein Out-of-Hospital Cardiac Arrest Registry template

The Utstein Out-of-Hospital Cardiac Arrest Resuscitation Registry Template, introduced in 1991 and updated in 2004 and 2015, standardizes data collection to enable research, evaluation, and comparisons of systems of care. The impetus for the current update stemmed from significant advances in the field and insights from registry development and regional comparisons. This 2024 update involved representatives of the International Liaison Committee on Resuscitation and used a modified Delphi process. Every 2015 Utstein data element was reviewed for relevance, priority (core or supplemental), and improvement. New variables were proposed and refined. All changes were voted on for inclusion. The 2015 domains—system, dispatch, patient, process, and outcomes—were retained. Further clarity is provided for the definitions of out-of-hospital cardiac arrest attended resuscitation and attempted resuscitation. Changes reflect advancements in dispatch, early response systems, and resuscitation care, as well as the importance of prehospital outcomes. Time intervals such as emergency medical service response time now emphasize precise reporting of the times used. New flowcharts aid the reporting of system effectiveness for patients with an attempted resuscitation and system efficacy for the Utstein comparator group. Recognizing the varying capacities of emergency systems globally, the writing group provided a minimal dataset for settings with developing emergency medical systems. Supplementary variables are considered useful for research purposes. These revisions aim to elevate data collection and reporting transparency by registries and researchers and to advance international comparisons and collaborations. The overarching objective remains the improvement of outcomes for patients with out-of-hospital cardiac arrest.

High expectations: Civil society participation in conflict early warning and response systems of the AU, ECOWAS and IGAD

ABSTRACT Civil society organisation (CSO) participation in conflict early warning and response systems (CEWRS) of African intergovernmental organisations is expected to be beneficial to collect data, conduct analyses, and respond timeously to the potential escalation of violent conflict in a way that is relevant to local stakeholders. These high expectations contrast with CEWRS’ protracted operationalisation procedures, low capacity of many CSOs, and the challenges of integrating civil society into (inter)governmental structures, which militate against effective participation. This article considers the net effect of CSO participation, examining how CSOs contributed to data collection, analyses, early warning and responses of CEWRS in the AU, ECOWAS and IGAD, and assesses their participation models. The article finds that CSO participation is a long way from delivering on expectations. It argues that CSOs can only fully deliver by building independent CEWRS that complete early warning-response processes in parallel to the intergovernmental systems, as in West Africa.

International Narcotics Crime Status and Countermeasures: Focusing on Thailand and new drugs

creasing every year. According to the Supreme Prosecutors' Office, the number of drug offenders exceeded 10,000 in 2015 and increased to 18,395 in 2022. In particular, the number of teenagers using drugs nearly tripled from 119 in 2017 to 481 in 2022. In addition, with the revitalization of international exchange and the Internet, illegal distribution of drugs on the dark web and other Internet drugs has increased. New supply methods such as illegal distribution of medical narcotics have emerged, and drugs developed as analogues or inducers that avoid existing sanctions are being distributed as new types of narcotics, making it difficult to solve the problem. The country that has the greatest influence on drug crimes in Korea is Thailand. As of 2022, among foreign drug offenders, Thais accounted for the largest number at 779, and the largest number were smuggling offenders at 301. Meanwhile, the harmfulness of drugs causes various social problems such as crimes due to arousal, tolerance, and withdrawal symptoms. In particular, the number of drug offenders under the age of 29 is increasing, raising concerns about the future of the country. Drug crime measures to be taken together with Thailand include establishing measures by drug type, establishing and implementing an early response system for new drugs such as a temporary drug designation system, and operating a cooperation system to investigate and arrest drug crime distribution networks.

Strengthening global health security through health early warning systems: A literature review and case study

Disease transmission is dependent on a variety of factors, including the characteristics of an event, such as crowding and shared accommodations, the potential of participants having prolonged exposure and close contact with infectious individuals, the type of activities, and the characteristics of the participants, such as their age and immunity to infectious agents [1–3]. Effective control of outbreaks of infectious diseases requires rapid diagnosis and intervention in high-risk settings. As a result, syndromic and event-based surveillance may be used to enhance the responsiveness of the surveillance system [1]. In public health, surveillance is collecting, analyzing, and interpreting data across time to inform decision-making and aid policy implementation [1]. In this review article we aimed to provide an overview of the principles, types, uses, advantages, and limitations of surveillance systems and to highlight the importance of early warning systems in response to the information received by disease surveillance. The study conducted a comprehensive literature search using several databases, selecting, and reviewing 78 articles that covered different types of surveillance systems, their applications, and their impact on controlling infectious diseases. The article also presents a case study from the Hajj gathering, which highlighted the development, evaluation, and impact of early warning systems on response to the information received by disease surveillance. The study concludes that ongoing disease surveillance should be accompanied by well-designed early warning and response systems, and continuous efforts should be invested in evaluating and validating these systems to minimize the risk of reporting delays and reducing the risk of outbreaks.

Evaluation of a multi-component early warning system for pastoralist populations in Doolo zone, Ethiopia: mixed-methods study

BackgroundThis study evaluated an early warning, alert and response system for a crisis-affected population in Doolo zone, Somali Region, Ethiopia, in 2019–2021, with a history of epidemics of outbreak-prone diseases. To adequately cover an area populated by a semi-nomadic pastoralist, or livestock herding, population with sparse access to healthcare facilities, the surveillance system included four components: health facility indicator-based surveillance, community indicator- and event-based surveillance, and alerts from other actors in the area. This evaluation described the usefulness, acceptability, completeness, timeliness, positive predictive value, and representativeness of these components.MethodsWe carried out a mixed-methods study retrospectively analysing data from the surveillance system February 2019–January 2021 along with key informant interviews with system implementers, and focus group discussions with local communities. Transcripts were analyzed using a mixed deductive and inductive approach. Surveillance quality indicators assessed included completeness, timeliness, and positive predictive value, among others.Results1010 signals were analysed; these resulted in 168 verified events, 58 alerts, and 29 responses. Most of the alerts (46/58) and responses (22/29) were initiated through the community event-based branch of the surveillance system. In comparison, one alert and one response was initiated via the community indicator-based branch. Positive predictive value of signals received was about 6%. About 80% of signals were verified within 24 h of reports, and 40% were risk assessed within 48 h. System responses included new mobile clinic sites, measles vaccination catch-ups, and water and sanitation-related interventions. Focus group discussions emphasized that responses generated were an expected return by participant communities for their role in data collection and reporting. Participant communities found the system acceptable when it led to the responses they expected. Some event types, such as those around animal health, led to the community’s response expectations not being met.ConclusionsEvent-based surveillance can produce useful data for localized public health action for pastoralist populations. Improvements could include greater community involvement in the system design and potentially incorporating One Health approaches.

Enabling countries to manage outbreaks: statistical, operational, and contextual analysis of the early warning and response system (EWARS-csd) for dengue outbreaks.

Dengue is currently the fastest-spreading mosquito-borne viral illness in the world, with over half of the world's population living in areas at risk of dengue. As dengue continues to spread and become more of a health burden, it is essential to have tools that can predict when and where outbreaks might occur to better prepare vector control operations and communities' responses. One such predictive tool, the Early Warning and Response System for climate-sensitive diseases (EWARS-csd), primarily uses climatic data to alert health systems of outbreaks weeks before they occur. EWARS-csd uses the robust Distribution Lag Non-linear Model in combination with the INLA Bayesian regression framework to predict outbreaks, utilizing historical data. This study seeks to validate the tool's performance in two states of Colombia, evaluating how well the tool performed in 11 municipalities of varying dengue endemicity levels. The validation study used retrospective data with alarm indicators (mean temperature and rain sum) and an outbreak indicator (weekly hospitalizations) from 11 municipalities spanning two states in Colombia from 2015 to 2020. Calibrations of different variables were performed to find the optimal sensitivity and positive predictive value for each municipality. The study demonstrated that the tool produced overall reliable early outbreak alarms. The median of the most optimal calibration for each municipality was very high: sensitivity (97%), specificity (94%), positive predictive value (75%), and negative predictive value (99%; 95% CI). The tool worked well across all population sizes and all endemicity levels but had slightly poorer results in the highly endemic municipality at predicting non-outbreak weeks. Migration and/or socioeconomic status are factors that might impact predictive performance and should be further evaluated. Overall EWARS-csd performed very well, providing evidence that it should continue to be implemented in Colombia and other countries for outbreak prediction.

Chemical Trends in Sample Preparation for Nucleic Acid Amplification Testing (NAAT): A Review.

Nucleic acid amplification testing facilitates the detection of disease through specific genomic sequences and is attractive for point-of-need testing (PONT); in particular, the early detection of microorganisms can alert early response systems to protect the public and ecosystems from widespread outbreaks of biological threats, including infectious diseases. Prior to nucleic acid amplification and detection, extensive sample preparation techniques are required to free nucleic acids and extract them from the sample matrix. Sample preparation is critical to maximize the sensitivity and reliability of testing. As the enzymatic amplification reactions can be sensitive to inhibitors from the sample, as well as from chemicals used for lysis and extraction, avoiding inhibition is a significant challenge, particularly when minimising liquid handling steps is also desirable for the translation of the assay to a portable format for PONT. The reagents used in sample preparation for nucleic acid testing, covering lysis and NA extraction (binding, washing, and elution), are reviewed with a focus on their suitability for use in PONT.

Early warning and response system for dengue outbreaks: Moving from research to operational implementation in Mexico.

Dengue disease epidemics have increased in time and space due to climatic and non-climatic factors such as urbanization. In the absence of an effective vaccine, preventing dengue outbreak relies on vector control activities. Employing computerized tools to predict outbreaks and respond in advance has great potential for improving dengue disease control. Evidence of integrating or implementing such applications into control programs and their impact are scarce, and endemic countries demand for experience sharing and know-how transfer. Mexico has extensive experience of pre-validated EWARS (Early Warning And Response System), a tool that was developed in 2012 as part of a collaboration with the Special Program for Research and Training in Tropical Diseases Unit (TDR) at the World Health Organization and used at national level. The advancement of EWARS since 2014 and its stepwise integration into the national surveillance system has increased the appreciation of the need for integrated surveillance (including disease, vector and climate surveillance), and for linking inter-institutional and trans-sectoral information for holistic epidemiological intelligence. The integration of the EWARS software into the national surveillance platform in Mexico was a remarkable milestone and a successful experience. This manuscript describes the implementation process of EWARS in Mexico, which started in 2012 and further demonstrates benefits, threats, and opportunities of integrating EWARS into existing national surveillance programs.

Decision-support tools to build climate resilience against emerging infectious diseases in Europe and beyond.

Climate change is one of several drivers of recurrent outbreaks and geographical range expansion of infectious diseases in Europe. We propose a framework for the co-production of policy-relevant indicators and decision-support tools that track past, present, and future climate-induced disease risks across hazard, exposure, and vulnerability domains at the animal, human, and environmental interface. This entails the co-development of early warning and response systems and tools to assess the costs and benefits of climate change adaptation and mitigation measures across sectors, to increase health system resilience at regional and local levels and reveal novel policy entry points and opportunities. Our approach involves multi-level engagement, innovative methodologies, and novel data streams. We take advantage of intelligence generated locally and empirically to quantify effects in areas experiencing rapid urban transformation and heterogeneous climate-induced disease threats. Our goal is to reduce the knowledge-to-action gap by developing an integrated One Health-Climate Risk framework.

One Health Surveillance System in Gujarat, India: A Health Policy and Systems Research Protocol for Exploring the Cross-Sectoral Collaborations to Detect Emerging Threats at the Human-Animal-Environment Interface.

The close interaction between humans, animals and the ecosystem has been a reason for the emergence and re-emergence of zoonotic diseases worldwide. Zoonoses are estimated to be responsible for 2.5 billion human illnesses and 2.7 million deaths worldwide. Gujarat is a western state in India with more than 65 million people and 26 million livestock, and includes surveillance systems for humans and animals; however, more evidence is needed on joint collaborative activities and their effect on the early warning response for zoonoses. Thus, this study aims to investigate sectoral collaborations for early warning and response systems for emerging and re-emerging zoonoses, aiming to develop a One Health surveillance (OHS) system in Gujarat, India. This case study uses policy content analysis followed by qualitative and quantitative data collection among state- and district-level surveillance actors to provide insight into the current cross-sectoral collaborations among surveillance actors. It helps identify triggers and documents factors helpful in strengthening cross-sectoral collaborations among these systems and facilitates the establishment of an OHS system in Gujarat, India.

One Health early warning and response system for zoonotic diseases outbreaks: Emphasis on the involvement of grassroots actors.

Emerging and reemerging zoonotic diseases have become a global concern due to their frequent occurrence. Large delays between onset of emerging zoonotic disease outbreaks and their reporting and control are indicative of weak animal and human health systems. The objective of this paper is to tackle the time delay by suggesting a One Health Early Warning and Response System (OH-EWRS) aiming at improving the surveillance and notification of zoonotic diseases by strengthening 'bottom-up' approaches and systems for early detection, especially in hot spot areas where they emerge. In this conceptual paper, we searched online database including PubMed, Google and Google Scholar to explore the scientific landscape for zoonotic diseases and One Health Early Warning and Response Systems published in English up to December, 2020. In addition, the authors made use of their own expertise and critically reviewed the retrieved papers that were found to be of relevance as the three authors are experts in their own fields, coming from different backgrounds, but are all working to improve the prevention and control of zoonotic disease outbreak. The OH-EWRS advocates for collaboration between relevant stakeholders including nongovernmental organisations, country offices of international and intergovernmental technical organisations, governmental bodies, research institutes, the private sector and local communities with the aim of an integrated One Health prevention and control system. The OH-EWRS considers various priorities and objectives of the different stakeholders, taking into account possible conflict of interests and considering the need for trust, transparency and mutual benefits. Although the operationalisation, governance and institutionalisation of the OH-EWRS should be the responsibility of government bodies, inputs from and feedback to relevant stakeholders through a bottom-up and top-down approach are essential elements for the application of the successful operationalisation of a OH-EWRS.

Critical Failure Factors of Flood Early Warning and Response Systems (FEWRS): A Structured Literature Review and Interpretive Structural Modelling (ISM) Analysis

Flood warning and response systems are essential components of risk reduction strategies with the potential to reduce loss of life and impact on personal assets. However, recent flood incidents have caused significant loss of human lives due to failures in current flood warning and response mechanisms. These failures are broadly related to policies concerning, and governance aspects within, warning generation, the behaviour of communities in responding to early warnings, and weaknesses in associated tools and technologies used in communicating early warnings and responding. Capturing critical failure factors affecting flood warning and response systems can provide opportunities for making corrective measures and for developing a more advanced and futuristic system for early flood warnings. This paper reports the findings of a structured review that was conducted to identify critical failure factors in flood early warning and response systems. This study found twenty-four critical failure factors (CFFs). The interpretive structural modelling (ISM) approach conducted in this study resulted in identifying four different types of failure factors (autonomous, dependent, linkage, and independent) with varying dependence and driving powers. Analysis shows that governance, leadership, finance, standard operating procedures (SoP), and community engagement are the most dominating factors with the highest driving factor, which can overcome other dependent factors. The outcome of this review could be helpful for policymakers and practitioners in overcoming failure factors and implementing effective early warning and response systems.

Towards a leptospirosis early warning system in northeastern Argentina

Leptospirosis is a zoonotic disease with a high burden in Latin America, including northeastern Argentina, where flooding events linked to El Niño are associated with leptospirosis outbreaks. The aim of this study was to evaluate the value of using hydrometeorological indicators to predict leptospirosis outbreaks in this region. We quantified the effects of El Niño, precipitation, and river height on leptospirosis risk in Santa Fe and Entre Ríos provinces between 2009 and 2020, using a Bayesian modelling framework. Based on several goodness of fit statistics, we selected candidate models using a long-lead El Niño 3.4 index and shorter lead local climate variables. We then tested predictive performance to detect leptospirosis outbreaks using a two-stage early warning approach. Three-month lagged Niño 3.4 index and one-month lagged precipitation and river height were positively associated with an increase in leptospirosis cases in both provinces. El Niño models correctly detected 89% of outbreaks, while short-lead local models gave similar detection rates with a lower number of false positives. Our results show that climatic events are strong drivers of leptospirosis incidence in northeastern Argentina. Therefore, a leptospirosis outbreak prediction tool driven by hydrometeorological indicators could form part of an early warning and response system in the region.

Need for effective detection and early warnings for epidemic and pandemic preparedness planning in the context of multi-hazards: Lessons from the COVID-19 pandemic

The need for effective early detection and timely surveillance for a robust pandemic and epidemic early warning and preparedness has been widely discussed amidst the Covid-19 pandemic, which suddenly erupted worldwide. This need is further established by various other hazards reported in many countries amidst the COVID-19 pandemic. In addition, the failure of early detection of pathogens and their source of origin has been largely connected with global transmission and severe outbreaks in many contexts. Therefore, effective early detection , timely surveillance and early warning are key aspects of a successful response to an epidemic or pandemic. . Hence, this paper aims to identify key elements and stages of an effective epidemic and pandemic early warning (EW) and response system. Further, the paper analyses inter-connections of the elements of the early warning system, focusing on the COVID-19 and multi-hazard context. The systematic literature review method was used to collect data from electronic databases. Results suggest that epidemiological surveillance & detection, primary screening of raw data & information, risk and vulnerability assessments, prediction and decision-making, alerts & early warnings are critical components of epidemic and pandemic EW. In addition, response-control & mitigation, preparedness-preventive strategies, and reducing transmission , elimination and eradication of the disease are integrated components of the early warning and response ecosystem that largely depend on effective early warnings. The significance of integrating epidemic and pandemic EW with other EWs to operate as multi-hazard early warning systems is also analysed.

Placenta DNA methylation levels of the promoter region of the leptin receptor gene are associated with infant cortisol

The intrauterine environment and early life stress regulation are widely recognized as an early foundation for lifelong physical and mental health. Methylation of CpG sites in the placenta represents an epigenetic modification that can potentially affect placental function, influence fetal development, and ultimately impact the health of offspring by programming the hypothalamic-pituitary-adrenal (HPA) axis stress response during prenatal development. Leptin, an adipokine produced by the placenta, is essential for energy homeostasis. It is also epigenetically regulated by promoter DNA methylation. Mounting evidence suggests that leptin also affects the stress response system. Though heterogeneity in the early stress response system may influence life-long mental and physical health, few studies explicitly examine the heterogeneity in the newborn stress response system. Less is known about leptin's association with the human hypothalamic-pituitary-adrenocortical (HPA) axis early in life. This study sought to serve as a proof of concept study investigating the relationship between newborn cortisol output trajectories and placental leptin DNA methylation in 117 healthy newborns from socioeconomically and racially- and ethnically-diverse families. We characterized heterogeneity in newborn cortisol output during the NICU Network Neurobehavioral Scales exam in the first week of life with latent growth mixture models. We then evaluated whether leptin promoter (LEP) methylation in placental samples was associated with newborn cortisol trajectories. Our findings suggest that increased placental LEP methylation, which corresponds to decreased leptin production, is associated with infant cortisol trajectories marked by increased cortisol output in the NNNS exam. These results provide important insights into the role of placental leptin DNA methylation in human newborn HPA axis development and subsequent developmental origins of health and disease processes.

Study of flood mitigation system for improving the resilience of pluvial flood control of south Jakarta. (Case study: Ciledug raya, Cipulir.)

Flooding is the inability of the channel capacity to accept stormwater so that it overflows into the surrounding area. The main problem of flooding in Jakarta is not in the main channel but in micro drainage which is commonly known as pluvial flooding. This research was conducted to increase resilience (reduce the risk of flooding) by making a device that is able to handle floods that can reduce the height and time of flooding in a location where flooding occurs. Floods cause damage. The parameters that are very important in determining the damage are inundation height and inundation duration. The methodology used in this research is to combine early warning system and emergency response based on hydrology engineering, hydraulics engineering and data science. The approach taken is to use an emergency response using the help of an early warning system. The emergency response used in this study is based on a mobile pump and its equipment and power that can be moved at any time. The emergency response is to use an early warning by predicting the microphysical symptoms of clouds that occur in the atmosphere. Emergency response is needed to cooperate together with early warning system in pluvial flooding problem. Unifying early warning system and emergency response system that this research called flood device is able to reduce the depth and duration of inundation.

Design and Application of an Early Warning and Emergency Response System in the Transboundary Area of the Taihu Lake Basin.

The inter-provincial transboundary area of the Taihu Lake Basin is characterized by a complex river network and reciprocating flow. Frequent environmental pollution events in recent years have become a major safety hazard for the water quality in the Taihu Lake Basin. There are few early warning systems for environmental pollution events in China, the ability to simulate risk is insufficient, and systematic research on technology, development, and application is lacking. Thus, water management requirements are not met in the inter-provincial transboundary area of the Taihu Lake Basin. This paper proposes a cross-border risk management plan for pollution sources in the transboundary areas of the Taihu Lake Basin and an early warning and emergency response system for water pollution events using modern information technology. We used this system to assess and classify 2713 risk sources for nitrogen and phosphorus pollution into 5 categories. We simulated the discharge of a pollutant into a tributary and the early warning and emergency response for the transboundary region. The results indicate that the proposed early warning and emergency response system substantially improved the transboundary water environment and lowered the risk of pollution in the Taihu Lake watershed.