Detection of pathogenic viruses in the urban wastewater in Kuwait-implications for monitoring viral disease outbreaks

Effective surveillance for epidemic-prone viral diseases is essential for emergency preparedness to respond to threats and occurrences of pandemics. While it is difficult and expensive to conduct health facility-based surveillance, there is a growing interest in conducting sewage-based epidemiological studies to monitor the health of the urban population because of the relative ease of sample collection and the availability of advanced molecular techniques for the detection of pathogens in the sewage. Sewage samples offer unique means to study the aggregate health of the population as opposed to the monitoring of the health of any individual by traditional methods. We worked together with the Ministry of Public Works in Kuwait and developed a platform for the collection and testing of sewage samples from different regions of Kuwait for studying population health. In this report, we describe the results of a cross-sectional study conducted between 16 and 23 September 2019 in an attempt to detect influenza, Noro, Rota, hepatitis A, and hepatitis E viruses in urban sewage samples collected in Kuwait. All five targeted viruses were detected in the samples collected from urban wastewater in Kuwait using reverse-transcriptase quantitative PCR (RT-qPCR). We recently checked for the presence of SARS-CoV-2 in the stored cDNA samples and confirmed the absence of SARS-CoV-2 in them. This is the first report that demonstrates the preparedness in Kuwait for using sewage samples for the detection and monitoring of many pathogenic viruses which may greatly increase the capacity of the country to deal with a viral disease outbreak in the future.

Deep Similarity Analysis and Forecasting of Actual Outbreak of Major Infectious Diseases using Internet-Sourced Data

Perhaps no other generation in the span of recorded human history has endured the risks of infectious diseases as has the current generation. The prevalence of infectious diseases is caused mainly by unlimited contact between people in a highly globalized world. Disease control and prevention (CDC) promptly collect and produce disease outbreak statistics, but CDCs rely on a curated, centralized collection system, and requires up to two weeks of lead time. Consequently, the quick release of disease outbreak information has become a great challenge. Infectious disease outbreak information is recorded and spread somewhere on the Internet much faster than CDC announcements, and Internet-sourced data have shown non-substitutable potential to watch and predict infectious disease outbreaks in advance. In this study, we performed a thorough analysis to show the similarity between the Korean Center of Disease Control (KCDC) infectious disease datasets and three Internet-sourced data for nine major infectious diseases in terms of time-series volume. The results show that many of infectious disease outbreak have strongly related to Internet-sourced data. We analyzed several factors that affect the similarity. Our analysis shows that the increase in the number of Internet-sourced data correlates with the increase in the number of infected people and thus, show the positive similarity. We also found that the greater the number of infectious disease outbreaks corresponds to having a wider spread of outbreak regions, in which it also proves to have higher similarity. We presented the prediction result of infectious disease outbreak using various Internet-sourced data and an effective deep learning algorithm. It showed that there are positive correlations between the number of infected people or the number of related web data and the prediction accuracy. We developed and currently operate a web-based system to show the similarity between KCDC and related Internet-sourced data for infectious diseases. This paper helps people to identify what kind of Internet-sourced data they need to use to predict and track a specific infectious disease outbreak. We considered as much as nine major diseases and three kinds of Internet-sourced data together, and we can say that our finding did not depend on specific infectious disease nor specific Internet-sourced data.

Getting Critical Information During the COVID-19 Pandemic: Experiences of Spanish and Chinese Speakers With Limited English Proficiency

People with limited English proficiency in the United States have suffered disproportionate negative health outcomes during the COVID-19 pandemic. Effective communications are critical tools in addressing inequities insofar as they can motivate adoption of protective behaviors and reduce incidence of disease; however, little is known about experiences of communities with limited English proficiency receiving relevant information during COVID-19 or other outbreaks. To address this gap and provide inputs for communication strategies, we completed a study based on 2 novel and nationally representative surveys conducted between June and August 2020 among Spanish and Chinese speakers with limited English proficiency (n = 764 and n = 355, respectively). Results first showed that Spanish and Chinese speakers did not consistently receive information about protective behaviors from key public health and government institutions early in the pandemic. Second, for such information, Spanish and Chinese speakers used a diverse set of information resources that included family and friends, social media, and traditional media from both inside and outside the United States. Third, Spanish and Chinese speakers faced challenges getting COVID-19 information, including receiving media messages that felt discriminatory toward Latinx or Chinese people. Together, these findings suggest gaps in effectively reaching Spanish and Chinese speakers. Data highlight the important role of bilingual materials to support sharing of information between Spanish or Chinese speakers and English speakers within their social networks, and the need for digital news content for traditional and social media. Finally, efforts are needed to address discriminatory messaging in media and to actively counter it in public health communications.

Multisectoral cost analysis of a human and livestock anthrax outbreak in Songwe Region, Tanzania (December 2018-January 2019), using a novel Outbreak Costing Tool

OBJECTIVES

We applied a novel Outbreak Costing Tool (OCT), developed by the US Centers for Disease Control and Prevention (CDC), to estimate the costs of investigating and responding to an anthrax outbreak in Tanzania. We also evaluated the OCT's overall utility in its application to a multisectoral outbreak response.

METHODS

We collected data on direct costs associated with a human and animal anthrax outbreak in Songwe Region (December 2018 to January 2019) using structured questionnaires from key-informants. We performed a cost analysis by entering direct costs data into the OCT, grouped into seven cost categories: labor, office, travel and transport, communication, laboratory support, medical countermeasures, and consultancies.

RESULTS

The total cost for investigating and responding to this outbreak was estimated at 102,232 United States dollars (USD), with travel and transport identified as the highest cost category (62,536 USD) and communication and consultancies as the lowest, with no expenditure, for the combined human and animal health sectors.

CONCLUSIONS

Multisectoral investigation and response may become complex due to coordination challenges, thus allowing escalation of public health impacts. A standardized framework for collecting and analysing cost data is vital to understanding the nature of outbreaks, in anticipatory planning, in outbreak investigation and in reducing time to intervention. Pre-emptive use of the OCT will also reduce overall and specific (response period) intervention costs for the disease. Additional aggregation of the costs by government ministries, departments and tiers will improve the use of the tool to enhance sectoral budget planning for disease outbreaks in a multisectoral response.

Prioritizing zoonotic diseases using a multisectoral, One Health approach for The Economic Community of West African States (ECOWAS)

BACKGROUND

Zoonotic diseases pose a significant threat to human, animal, and environmental health. The Economic Community of West African States (ECOWAS) has endured a significant burden of zoonotic disease impacts. To address zoonotic disease threats in ECOWAS, a One Health Zoonotic Disease Prioritization (OHZDP) was conducted over five days in December 2018 to prioritize zoonotic diseases of greatest regional concern and develop next steps for addressing these priority zoonoses through a regional, multisectoral, One Health approach.

METHODS

The OHZDP Process uses a mixed methods prioritization process developed by the United States Centers for Disease Control and Prevention. During the OHZDP workshop, representatives from human, animal, and environmental health ministries from all 15 ECOWAS Member States used a transparent and equal process to prioritize endemic and emerging zoonotic diseases of greatest regional concern that should be jointly addressed by One Health ministries and other partners. After the priority zoonotic diseases were identified, participants discussed recommendations and further regional actions to address the priority zoonoses and advance One Health in the region.

RESULTS

ECOWAS Member States agreed upon a list of seven priority zoonotic diseases for the region - Anthrax, Rabies, Ebola and other viral hemorrhagic fevers (for example, Marburg fever, Lassa fever, Rift Valley fever, Crimean-Congo Hemorrhagic fever), zoonotic influenzas, zoonotic tuberculosis, Trypanosomiasis, and Yellow fever. Participants developed recommendations and further regional actions that could be taken, using a One Health approach to address the priority zoonotic diseases in thematic areas including One Health collaboration and coordination, surveillance and laboratory, response and preparedness, prevention and control, workforce development, and research.

CONCLUSIONS

ECOWAS was the first region to use the OHZDP Process to prioritize zoonotic disease of greatest concern. With identified priority zoonotic diseases for the region, ECOWAS Member States can collaborate more effectively to address zoonotic diseases threats across the region using a One Health approach. Strengthening national and regional level multisectoral, One Health Coordination Mechanisms will allow ECOWAS Member States to advance One Health and have the biggest impact on improving health outcomes for both people and animals living in a shared environment.

Impact of Kenya's Frontline Epidemiology Training Program on Outbreak Detection and Surveillance Reporting: A Geographical Assessment, 2014-2017

Rapid detection and response to infectious disease outbreaks requires a robust surveillance system with a sufficient number of trained public health workforce personnel. The Frontline Field Epidemiology Training Program (Frontline) is a focused 3-month program targeting local ministries of health to strengthen local disease surveillance and reporting capacities. Limited literature exists on the impact of Frontline graduates on disease surveillance completeness and timeliness reporting. Using routinely collected Ministry of Health data, we mapped the distribution of graduates between 2014 and 2017 across 47 Kenyan counties. Completeness was defined as the proportion of complete reports received from health facilities in a county compared with the total number of health facilities in that county. Timeliness was defined as the proportion of health facilities submitting surveillance reports on time to the county. Using a panel analysis and controlling for county-fixed effects, we evaluated the relationship between the number of Frontline graduates and priority disease reporting of measles. We found that Frontline training was correlated with improved completeness and timeliness of weekly reporting for priority diseases. The number of Frontline graduates increased by 700%, from 57 graduates in 2014 to 456 graduates in 2017. The annual average rates of reporting completeness increased from 0.8% in 2014 to 55.1% in 2017. The annual average timeliness reporting rates increased from 0.1% in 2014 to 40.5% in 2017. These findings demonstrate how global health security implementation progress in workforce development may influence surveillance and disease reporting.

Experiences and needs of nursing students during pandemic outbreaks: A systematic overview of the literature

Background

Recent epidemics have placed overwhelming demands on health systems, leading at times to the deployment of nursing students during the crisis. Little is known about the impact this experience has on students. Although studies have explored nursing students' knowledge about infection control, there are no specific recommendations regarding how these issues should be addressed in nurse education.

Purpose

To conduct a comprehensive systematic overview of the literature concerning nursing students in the context of emerging infectious disease epidemics or pandemics caused by zoonotic viruses.

Methods

Systematic overview.

Results

Forty-eight articles were included. Five themes were identified: education; knowledge, concern about risk and preventive behaviour; willingness to work during a pandemic outbreak; experiences and emotional impact; and ethical dilemmas.

Conclusions

There is a need to enhance nurse education to ensure that students have adequate education in infection prevention and control and the opportunity to develop the skills and attitudes required to provide care to infected patients during a pandemic. The outcomes of these education programmes would need to be evaluated using valid and reliable instruments so as to enable comparisons to be made to prepare future nurses to deal with new pandemics in an increasingly globalized world.

Defining facets of social distancing during the COVID-19 pandemic: Twitter analysis

Objectives

Using Twitter, we aim to (1) define and quantify the prevalence and evolution of facets of social distancing during the COVID-19 pandemic in the US in a spatiotemporal context and (2) examine amplified tweets among social distancing facets.

Materials and methods

We analyzed English and US-based tweets containing “coronavirus” between January 23-March 24, 2020 using the Twitter API. Tweets containing keywords were grouped into six social distancing facets: implementation, purpose, social disruption, adaptation, positive emotions, and negative emotions.

Results

A total of 259,529 unique tweets were included in the analyses. Social distancing tweets became more prevalent from late January to March but were not geographically uniform. Early facets of social distancing appeared in Los Angeles, San Francisco, and Seattle: the first cities impacted by the COVID-19 outbreak. Tweets related to the “implementation” and “negative emotions” facets largely dominated in combination with topics of “social disruption” and “adaptation”, albeit to lesser degree. Social disruptiveness tweets were most retweeted, and implementation tweets were most favorited.

Discussion

Social distancing can be defined by facets that respond to and represent certain events in a pandemic, including travel restrictions and rising case counts. For example, Miami had a low volume of social distancing tweets but grew in March corresponding with the rise of COVID-19 cases.

Conclusion

The evolution of social distancing facets on Twitter reflects actual events and may signal potential disease hotspots. Our facets can also be used to understand public discourse on social distancing which may inform future public health measures.

[Development and applications of makeshift emergency hospitals]

When wars, major disasters, or epidemics of the infectious diseases occur, existing medical facilities are usually unable to implement timely and effective treatment for patients, or the reception capacity is difficult to meet the surge in demand for health care. The makeshift emergency hospitals are built for patient reception, treatment and even isolation for infectious disease control. The makeshift hospitals have developed and improved in modern times, including mobile field hospitals, field tent hospitals and navy hospital ships equipped with advanced equipment and commonly used for military purposes, or temporary hospitals built in large public buildings and newly built hospitals in support of disaster relief and humanitarian operation. Makeshift hospitals have played an important role in response to many disasters and epidemics globally. This paper briefly summarizes the history, types, and applications of makeshift hospitals in disasters and epidemic responses.

Response Measures to Infection Outbreaks During the Second Year of Sustenance Phase of Infection Control Quality Improvement

OBJECTIVE

To analyze the infection outbreaks, control measures and outcomes of the outbreak in the NICU of a tertiary care centre in the year 2018.

METHODS

This study was conducted in a 30 bedded tertiary care NICU from January 2018 through December 2018. The study design was an Outbreak investigation, based on a program of prospective surveillance for nosocomial infection. All neonates admitted to the NICU formed part of the the study. An Infection Control Quality Improvement (QI) team was available to analyze the infection and initiate response action to outbreaks.

RESULTS

Three outbreaks were reported in the year 2018. The first was in May 2018 and comprised of colonization with rectal Multi-drug resistant gram negative bacilli (MDR GNB). The outbreak was controlled by using Aseptic non-touch technique (ANTT) for fortification of milk and using distilled water for cleaning of diaper area. The second outbreak in August 2018 was Methicillin resistant Staphylococcus aureus (MRSA) whose source was a maternal Lower segment cesarean section (LSCS) wound. The third outbreak in October 2018 was MDR Acinetobacter. The source was from an outborn having the same organism. All infants were in close proximity to the index case. This outbreak was controlled with cohorting, hand hygiene and strengthening of bundle care.

CONCLUSIONS

Surveillance aids in early detection and successful control of outbreaks. A systematic search for the source and meticulous containment of spread can successfully control an outbreak.

How to improve adherence with quarantine: rapid review of the evidence

OBJECTIVES

The December 2019 outbreak of coronavirus has once again thrown the vexed issue of quarantine into the spotlight, with many countries asking their citizens to 'self-isolate' if they have potentially come into contact with the infection. However, adhering to quarantine is difficult. Decisions on how to apply quarantine should be based on the best available evidence to increase the likelihood of people adhering to protocols. We conducted a rapid review to identify factors associated with adherence to quarantine during infectious disease outbreaks.

STUDY DESIGN

The study design is a rapid evidence review.

METHODS

We searched Medline, PsycINFO and Web of Science for published literature on the reasons for and factors associated with adherence to quarantine during an infectious disease outbreak.

RESULTS

We found 3163 articles and included 14 in the review. Adherence to quarantine ranged from as little as 0 up to 92.8%. The main factors which influenced or were associated with adherence decisions were the knowledge people had about the disease and quarantine procedure, social norms, perceived benefits of quarantine and perceived risk of the disease, as well as practical issues such as running out of supplies or the financial consequences of being out of work.

CONCLUSIONS

People vary in their adherence to quarantine during infectious disease outbreaks. To improve this, public health officials should provide a timely, clear rationale for quarantine and information about protocols; emphasise social norms to encourage this altruistic behaviour; increase the perceived benefit that engaging in quarantine will have on public health; and ensure that sufficient supplies of food, medication and other essentials are provided.

[Development and applications of makeshift emergency hospitals]

When wars, major disasters, or epidemics of the infectious diseases occur, existing medical facilities are usually unable to implement timely and effective treatment for patients, or the reception capacity is difficult to meet the surge in demand for health care. The makeshift emergency hospitals are built for patient reception, treatment, and even isolation for infectious disease control. The makeshift hospitals have developed and improved in modern times, including mobile field hospitals, field tent hospitals, and navy hospital ships equipped with advanced equipment and commonly used for military purposes or in support of disaster relief and humanitarian operation, and temporary hospitals built in large public buildings, and newly built hospitals. Makeshift hospitals have played an important role in response to many disasters and epidemics globally. This paper briefly summarizes the history, types, and applications of makeshift hospitals in disaster and epidemic response.

Time-optimal control strategies in SIR epidemic models

We investigate the time-optimal control problem in SIR (Susceptible-Infected-Recovered) epidemic models, focusing on different control policies: vaccination, isolation, culling, and reduction of transmission. Applying the Pontryagin's Minimum Principle (PMP) to the unconstrained control problems (i.e. without costs of control or resource limitations), we prove that, for all the policies investigated, only bang-bang controls with at most one switch are admitted. When a switch occurs, the optimal strategy is to delay the control action some amount of time and then apply the control at the maximum rate for the remainder of the outbreak. This result is in contrast with previous findings on the unconstrained problems of minimizing the total infectious burden over an outbreak, where the optimal strategy is to use the maximal control for the entire epidemic. Then, the critical consequence of our results is that, in a wide range of epidemiological circumstances, it may be impossible to minimize the total infectious burden while minimizing the epidemic duration, and vice versa. Moreover, numerical simulations highlighted additional unexpected results, showing that the optimal control can be delayed also when the control reproduction number is lower than one and that the switching time from no control to maximum control can even occur after the peak of infection has been reached. Our results are especially important for livestock diseases where the minimization of outbreaks duration is a priority due to sanitary restrictions imposed to farms during ongoing epidemics, such as animal movements and export bans.

African swine fever outbreak on a medium-sized farm in Uganda: biosecurity breaches and within-farm virus contamination

In Uganda, a low-income country in east Africa, African swine fever (ASF) is endemic with yearly outbreaks. In the prevailing smallholder subsistence farming systems, farm biosecurity is largely non-existent. Outbreaks of ASF, particularly in smallholder farms, often go unreported, creating significant epidemiological knowledge gaps. The continuous circulation of ASF in smallholder settings also creates biosecurity challenges for larger farms. In this study, an on-going outbreak of ASF in an endemic area was investigated on farm level, including analyses of on-farm environmental virus contamination. The study was carried out on a medium-sized pig farm with 35 adult pigs and 103 piglets or growers at the onset of the outbreak. Within 3 months, all pigs had died or were slaughtered. The study included interviews with farm representatives as well as biological and environmental sampling. ASF was confirmed by the presence of ASF virus (ASFV) genomic material in biological (blood, serum) and environmental (soil, water, feed, manure) samples by real-time PCR. The ASFV-positive biological samples confirmed the clinical assessment and were consistent with known virus characteristics. Most environmental samples were found to be positive. Assessment of farm biosecurity, interviews, and the results from the biological and environmental samples revealed that breaches and non-compliance with biosecurity protocols most likely led to the introduction and within-farm spread of the virus. The information derived from this study provides valuable insight regarding the implementation of biosecurity measures, particularly in endemic areas.

What caused the 2012 dengue outbreak in Pucallpa, Peru? A socio-ecological autopsy

Dengue is highly endemic in Peru, with increases in transmission particularly since vector re-infestation of the country in the 1980s. Pucallpa, the second largest city in the Peruvian Amazon, experienced a large outbreak in 2012 that caused more than 10,000 cases and 13 deaths. To date, there has been limited research on dengue in the Peruvian Amazon outside of Iquitos, and no published review or critical analysis of the 2012 Pucallpa dengue outbreak. This study describes the incidence, surveillance, and control of dengue in Ucayali to understand the factors that contributed to the 2012 Pucallpa outbreak. We employed a socio-ecological autopsy approach to consider distal and proximal contributing factors, drawing on existing literature and interviews with key personnel involved in dengue control, surveillance and treatment in Ucayali. Spatio-temporal analysis showed that relative risk of dengue was higher in the northern districts of Calleria (RR = 2.18), Manantay (RR = 1.49) and Yarinacocha (RR = 1.25) compared to all other districts between 2004 and 2014. The seasonal occurrence of the 2012 outbreak is consistent with typical seasonal patterns for dengue incidence in the region. Our assessment suggests that the outbreak was proximally triggered by the introduction of a new virus serotype (DENV-2 Asian/America) to the region. Increased travel, rapid urbanization, and inadequate water management facilitated the potential for virus spread and transmission, both within Pucallpa and regionally. These triggers occurred within the context of failures in surveillance and control programming, including underfunded and ad hoc vector control. These findings have implications for future prevention and control of dengue in Ucayali as new diseases such as chikungunya and Zika threaten the region.

Structural Factors of the Middle East Respiratory Syndrome Coronavirus Outbreak as a Public Health Crisis in Korea and Future Response Strategies

The recent Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak has originated from a failure in the national quarantine system in the Republic of Korea as most basic role of protecting the safety and lives of its citizens. Furthermore, a number of the Korean healthcare system's weaknesses seem to have been completely exposed. The MERS-CoV outbreak can be considered a typical public health crisis in that the public was not only greatly terrorized by the actual fear of the disease, but also experienced a great impact to their daily lives, all in a short period of time. Preparedness for and an appropriate response to a public health crisis require comprehensive systematic public healthcare measures to address risks comprehensively with an all-hazards approach. Consequently, discussion regarding establishment of post-MERS-CoV improvement measures must focus on the total reform of the national quarantine system and strengthening of the public health infrastructure. In addition, the Korea Centers for Disease Control and Prevention must implement specific strategies of action including taking on the role of "control tower" in a public health emergency, training of Field Epidemic Intelligence Service officers, establishment of collaborative governance between central and local governments for infection prevention and control, strengthening the roles and capabilities of community-based public hospitals, and development of nationwide crisis communication methods.

Discovery of a missing disease spreader

This study presents a method to discover an outbreak of an infectious disease in a region for which data are missing, but which is at work as a disease spreader. Node discovery for the spread of an infectious disease is defined as discriminating between the nodes which are neighboring to a missing disease spreader node, and the rest, given a dataset on the number of cases. The spread is described by stochastic differential equations. A perturbation theory quantifies the impact of the missing spreader on the moments of the number of cases. Statistical discriminators examine the mid-body or tail-ends of the probability density function, and search for the disturbance from the missing spreader. They are tested with computationally synthesized datasets, and applied to the SARS outbreak and flu pandemic.