Early Warning Alert Research Articles

Uncertainty in Ground-Motion-to-Intensity Conversions Significantly Affects Earthquake Early Warning Alert Regions

Abstract We examine how the choice of ground-motion-to-intensity conversion equations (GMICEs) in earthquake early warning (EEW) systems affects resulting alert regions. We find that existing GMICEs can underestimate observed shaking at short rupture distances or overestimate the extent of low-intensity shaking. Updated GMICEs that remove these biases would improve the accuracy of alert regions for the ShakeAlert EEW system for the West Coast of the United States. ShakeAlert uses ground-motion prediction equations (GMPEs), which calculate spatial distributions of peak ground acceleration (PGA) and peak ground velocity (PGV) from earthquake source estimates, combined with GMICEs to translate GMPE output into modified Mercalli intensity (MMI). We find significant epistemic uncertainty in alert distances; near-source MMI estimates from different GMICEs can differ by over 1 MMI unit, and MMI extents used for public EEW alerts can differ by hundreds of kilometers for larger magnitude earthquakes (M ∼6.5+). We use a catalog of “Did You Feel It?” shaking reports to evaluate how well GMICEs predict observed shaking. Our preferred GMICE is the one that computes MMI using PGV for high intensities and transitions to using PGA for nondamaging intensities. These results motivate updating GMICE relationships more generally, including in ShakeMap applications.

Premerger Sky Localization of Gravitational Waves from Binary Neutron Star Mergers Using Deep Learning

The simultaneous observation of gravitational waves (GW) and prompt electromagnetic counterparts from the merger of two neutron stars can help reveal the properties of extreme matter and gravity during and immediately after the final plunge. Rapid sky localization of these sources is crucial to facilitate such multimessenger observations. As GWs from binary neutron star (BNS) mergers can spend up to 10–15 minutes in the frequency bands of the detectors at design sensitivity, early-warning alerts and premerger sky localization can be achieved for sufficiently bright sources, as demonstrated in recent studies. In this work, we present premerger BNS sky localization results using GW-SkyLocator, a deep-learning model capable of inferring sky location posterior distributions of GW sources at orders of magnitude faster speeds than standard Markov Chain Monte Carlo methods. We test our model’s performance on a catalog of simulated injections from Sachdev, recovered at 0–60 s before the merger, and obtain comparable sky localization areas to the rapid localization tool BAYESTAR. These results show the feasibility of our model for premerger sky localization and the possibility of follow-up observations for precursor emissions from BNS mergers.

A review on foodborne disease outbreaks in Bhutan.

Foodborne diseases (FBDs) are a public health threat that can result in loss of lives and are a hurdle to socioeconomic development. The Foodborne Disease Burden Epidemiology Reference Group estimated that the annual burden of FBDs in the South-East Asia Region was more than 150 million illnesses, causing about 175,000 deaths. This review paper aims to compile evidence from the published articles and gray literatures on food-related disease outbreaks in Bhutan. Information was generated from the annual health bulletin published by the Ministry of Health and data from the National Early Warning Alert Response Surveillance and Information System hosted by Royal Centre for Disease Control. The laboratory confirmation rate of FBD investigation outbreaks increased from 25.5% (2012-2018) to 91.7% in 2020, as per the National Food Safety Indicator (FSI). At least 0.15% of the total population had suffered FBD from 2015 to 2020, and the baseline report shows that most of the FBD events occurred during hot and wet seasons (June and August). The common pathogen causing FBD was Salmonella species accounting for 42.9% of cases, followed by Shigella species (21.4%). Most of the FBD events were reported in schools (46.5%). The frequency of the reported FBD outbreaks had increased from 8 events in 2015 to 15 events in 2017 and 10 events in 2018. The study confirms the improved surveillance for FBDs in Bhutan and highlights the need to raise public awareness on food safety.

Establishing communicable disease surveillance systems

Humanitarian emergencies can result in an increase of communicable diseases, leading to a rise in mortality and/or morbidity in vulnerable populations. This requires a public health approach to re-establish control...

Psychological Effects of Dominant Responses to Early Warning Alerts

Earthquake-related behaviors in Mexico and Japan have highlighted the need to better understand responses to demanding alerting scenarios. Both countries appear to have benefitted from an established early earthquake warning system for several years. However, recent alert responses documented in these settings have been unlikely to protect residents from death or severe injury. This represents a gap between alerting system investments and effectiveness which, among other implications, could result in very large numbers of avoidable injuries and even deaths. To help better understand and address this gap, the current paper presents a theoretical explanation of why alerted residents have responded in the ways that they did. Behavioral and cognitive theories are discussed towards an integrated but simple model of alert response behavior that can be used to guide further research. Challenges and opportunities for this further research are also outlined.

An Early-warning System for Electromagnetic Follow-up of Gravitational-wave Events

Abstract Binary neutron stars (BNSs) will spend ≃10–15 minutes in the band of Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo detectors at design sensitivity. Matched-filtering of gravitational-wave (GW) data could in principle accumulate enough signal-to-noise ratio (S/N) to identify a forthcoming event tens of seconds before the companions collide and merge. Here we report on the design and testing of an early-warning GW detection pipeline. Early-warning alerts can be produced for sources that are at low enough redshift so that a large enough S/N accumulates ∼10–60 s before merger. We find that about 7% (49%) of the total detectable BNS mergers will be detected 60 s (10 s) before the merger. About 2% of the total detectable BNS mergers will be detected before merger and localized to within 100 deg2 (90% credible interval). Coordinated observing by several wide-field telescopes could capture the event seconds before or after the merger. LIGO–Virgo detectors at design sensitivity could facilitate observing at least one event at the onset of merger.

Optimizing Earthquake Early Warning Alert Distance Strategies Using the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, Earthquakes

ABSTRACTThe ShakeAlert earthquake early warning system aims to alert people who experience modified Mercalli intensity (MMI) IV+ shaking during an earthquake using source estimates (magnitude and location) to estimate median-expected peak ground motions with distance, then using these ground motions to determine median-expected MMI and thus the extent of MMI IV shaking. Because median ground motions are used, even if magnitude and location are correct, there will be people outside the alert region who experience MMI IV shaking but do not receive an alert (missed alerts). We use 91,000 “Did You Feel It?” survey responses to the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, earthquakes to determine which ground-motion to intensity conversion equation (GMICE) best fits median MMI with distance. We then explore how incorporating uncertainty from the ground-motion prediction equation and the GMICE in the alert distance calculation can produce more accurate MMI IV alert regions for a desired alerting strategy (e.g., aiming to alert 95% of people who experience MMI IV+ shaking), assuming accurate source characterization. Without incorporating ground-motion uncertainties, we find MMI IV alert regions using median-expected ground motions alert fewer than 20% of the population that experiences MMI IV+ shaking. In contrast, we find >94% of the people who experience MMI IV+ shaking can be included in the MMI IV alert region when two standard deviations of ground-motion uncertainty are included in the alert distance computation. The optimal alerting strategy depends on the false alert tolerance of the community due to the trade-off between minimizing missed and false alerts. This is especially the case for situations like the Mw 6.4 earthquake when alerting 95% of the 5 million people who experience MMI IV+ also results in alerting 14 million people who experience shaking below this level and do not need to take protective action.

Active and syndromic surveillance for mass gatherings: BOOM festival 2018, Portugal

Purpose: To describe the implementation and results of an active syndromic surveillance team in a planned and recurrent international mass gathering (MG) allowing early detection of outbreaks, and thereby, allowing intervention by local, national and international authorities. Methods & Materials: A field team of 17 health-care workers performed active and syndromic surveillance at Boom Festival 2018 between 21st and 29th of July 2018, in Portugal. Data including demographic characteristics, signs, symptoms, and environmental exposure was collected during admission at Boom Medical Service (BMS). Paper records were transcribed and analyzed with Microsoft Excel® 2016 (v 16.0). Descriptive analysis was performed and reported daily to relevant stakeholders. Results: Approximately 30,000 people from 147 countries attended the BOOM Festival, and 3,100 healthcare episodes occurred, including 451 (14.5%) complaints of gastrointestinal symptoms. During the Festival, there was a considerable increase in the incidence of gastrointestinal symptoms and an early warning alert for a possible outbreak of acute gastroenteritis was issued to the national health authorities on 24th of July. Interventions were carried out in collaboration with local public health authorities to control the outbreak and to address possible common-sources of infection. Contaminated food or water were suspected, and a person-to-person transmission was not excluded since several cases mentioned attending another MG and symptom onset before arrival at the festival. The concern about an early stage outbreak was valid since 62.5% (n = 282) of the cases with gastrointestinal symptoms were reported between 26th-29th of July. Conclusion: Active and syndromic surveillance are essential for timely data collection and analysis in MGs, delivering a comprehensive snapshot of daily incidents, enabling rapid response to possible outbreaks and providing early-warning alerts for stakeholders. Nevertheless, enhancements are needed: data sharing and improved communication channels between stakeholders and similar international MG are necessary to create an effective syndromic surveillance system. Author response to letter from Gomez et al.International Journal of Infectious DiseasesVol. 91PreviewThe abstract by Maki et al. (2019) contained limited information from a poster presented in a late-breaking session at the Seventh International Meeting on Emerging Diseases and Surveillance. The work had IRB approval (HFHS #12383), and informed consent was obtained prior to collecting samples. Full-Text PDF Open AccessBacterial colonization in point-of-use filters and deaths in Flint, MichiganInternational Journal of Infectious DiseasesVol. 91PreviewThe study by Maki et al. (2019) examined the effects of point-of-use (PoU) filters on bacterial infections in residents of Flint, Michigan homes. The authors noted that 12 pathogens (including Pseudomonas aeruginosa) were detected in PoU filters in 10 Flint homes and that residents of 70% of these homes had severe respiratory infections. Additionally alarming, the authors reported an astounding 50% mortality rate in their study sample. Full-Text PDF Open Access

Outbreak of trichinellosis related to eating imported wild boar meat, Belgium, 2014.

Trichinellosis is a rare parasitic zoonosis caused by Trichinella following ingestion of raw or undercooked meat containing Trichinella larvae. In the past five years, there has been a sharp decrease in human trichinellosis incidence rates in the European Union due to better practices in rearing domestic animals and control measures in slaughterhouses. In November 2014, a large outbreak of trichinellosis occurred in Belgium, related to the consumption of imported wild boar meat. After a swift local public health response, 16 cases were identified and diagnosed with trichinellosis. Of the 16 cases, six were female. The diagnosis was confirmed by serology or the presence of larvae in the patients’ muscle biopsies by histology and/or PCR. The ensuing investigation traced the wild boar meat back to Spain. Several batches of imported wild boar meat were recalled but tested negative. The public health investigation allowed us to identify clustered undiagnosed cases. Early warning alerts and a coordinated response remain indispensable at a European level.

National dengue surveillance in the Lao People's Democratic Republic, 2006-2012: epidemiological and laboratory findings.

Although dengue has been a public health problem for several decades in the Lao People's Democratic Republic, the magnitude of the disease burden and epidemiological trends remain poorly understood. We analysed national dengue surveillance and laboratory data from 2006 to 2012 by person, place and time. Between 2006 and 2012, the annual dengue notification rate ranged between 62 and 367 cases per 100000 population with an apparent geographical expansion of transmission throughout the country in recent years and concurrent co-circulation of all four dengue virus subtypes. An electronic database, called Lao People's Democratic Republic Early Warning Alert and Response Network, was introduced in 2008 to provide automated early warning for outbreaks and epidemics. Village outbreaks continue to be notified primarily through event-based surveillance, whereas the weekly indicator-based system provides systematic assessment of annual epidemic cycles. The dengue case data indicate a high and increasing burden of disease. Efforts now need to focus on using available data to prompt more effective outbreak response and to guide the design and implementation of intervention strategies.

Timeliness of Data Delivery from Q330 Systems

Research in rapid analysis of earthquake data, broadly classified as early warning (EW) or early alarm studies, has spurred interest in the capability of digital seismic data systems to provide low‐latency data. Because of the wide usage of Quanterra Q330 data systems in operational networks, published results analyzing the latency of deployed systems have considered these devices. Several years ago, studies (e.g., Allen, 2009; Brown et al. , 2011) showed that the effectiveness of EW systems was then limited by the total delay required to deliver waveform data for analysis of 4 s or more within instrumentation systems. Recent results (Kuyuk et al. , 2014), however, following the American Recovery and Reinvestment Act (ARRA)‐funded upgrade of instrumentation in California show that instrumentation‐related delays have been reduced in some operational networks to a comparatively small component, typically <10%, of the overall time required to issue EW alerts. We present a simple, robust method to measure the latency of data delivery arising in the Q330 family of data loggers, including the typical contribution to total latency of both hardwired and cellular wireless communication paths over the public internet. These latter two categories of communication represent the majority of those used in operational seismological networks. Current EW systems are capable of issuance of an alert within 8.68±3.73 s after the first P ‐wave detection for events in California (Kuyuk et al. , 2014). We show that the actual latency introduced by Q330 data loggers—including public internet latencies—is typically <1.5 s maximum, with a mean value <1 s, when communications network bandwidth is capable of sustaining continuous data delivery. The method is applicable to any data system. Measured values of data latency are consistent with in situ measurements in EW systems now operating in California. The sub‐1 s mean latency capability of Q330 systems now deployed widely in seismically active areas …

Lessons learned from ten investigations of waterborne gastroenteritis outbreaks, France, 1998–2006

Ten outbreaks of waterborne acute gastroenteritis (AGE) have been investigated in France since 1998. These outbreaks have affected populations of over 1,000 people, with generally high attack rates. The causal agents have been identified in six of these events. Aetiologies involved mainly noroviruses and Cryptosporidium sp. The point of entry of the contamination was located in the distribution network in five outbreaks (waste water backflows in four cases and one case of contamination induced by maintenance work) and at the water collection facilities in five other cases. Once the outbreak was detected, epidemiological and environmental investigations and crisis management followed well-established procedures. Further progress in public health surveillance will depend on more complete and rapid detection and reporting. Automated analysis of health insurance data on the reimbursement of drugs for AGE should help make detection more complete. Improved reactivity depends primarily on the operator immediately reporting incidents that indicate a possible massive contamination of the water network to health authorities - in particular complaints from the population, which are the only early-warning alerts in the case of waste water backflows.

Panel 2.2: Surveillance, Early Warning Alert, and Response: Communicable and Vector-Borne Diseases

This is a summary of the presentations and discussion of Surveillance, Early Warning Alert and Response at the Conference, Health Aspects of the Tsunami Disaster in Asia, convened by the World Health Organization (WHO) in Phuket, Thailand, 04-06 May 2005. The topics discussed included issues related to the surveillance, early warning alert, and response to communicable and vector-borne diseases as pertaining to the responses to the damage created by the Tsunami. It is presented in the following major sections: (1) key questions; (2) needs assessment; (3) coordination; (4) gap filling; and (5) capacity building. The key questions section is presented in six sub-sections: (1) communicable diseases; (2) early warning; (3) laboratory capacity and referral networking; (4) coordination of disease surveillance, early warning, and response; (5) health infrastructure rebuilding; and (6) using existing national surveillance plans to enhance disease surveillance and early warning systems.