The impact of anthropogenic climate change on pediatric viral diseases

The adverse effects of climate change on human health are unfolding in real time. Environmental fragmentation is amplifying spillover of viruses from wildlife to humans. Increasing temperatures are expanding mosquito and tick habitats, introducing vector-borne viruses into immunologically susceptible populations. More frequent flooding is spreading water-borne viral pathogens, while prolonged droughts reduce regional capacity to prevent and respond to disease outbreaks with adequate water, sanitation, and hygiene resources. Worsening air quality and altered transmission seasons due to an increasingly volatile climate may exacerbate the impacts of respiratory viruses. Furthermore, both extreme weather events and long-term climate variation are causing the destruction of health systems and large-scale migrations, reshaping health care delivery in the face of an evolving global burden of viral disease. Because of their immunological immaturity, differences in physiology (e.g., size), dependence on caregivers, and behavioral traits, children are particularly vulnerable to climate change. This investigation into the unique pediatric viral threats posed by an increasingly inhospitable world elucidates potential avenues of targeted programming and uncovers future research questions to effect equitable, actionable change. IMPACT: A review of the effects of climate change on viral threats to pediatric health, including zoonotic, vector-borne, water-borne, and respiratory viruses, as well as distal threats related to climate-induced migration and health systems. A unique focus on viruses offers a more in-depth look at the effect of climate change on vector competence, viral particle survival, co-morbidities, and host behavior. An examination of children as a particularly vulnerable population provokes programming tailored to their unique set of vulnerabilities and encourages reflection on equitable climate adaptation frameworks.

Exploring Coronavirus Disease 2019 Vaccine Hesitancy on Twitter Using Sentiment Analysis and Natural Language Processing Algorithms

BACKGROUND

Vaccination can help control the coronavirus disease 2019 (COVID-19) pandemic but is undermined by vaccine hesitancy. Social media disseminates information and misinformation regarding vaccination. Tracking and analyzing social media vaccine sentiment could better prepare health professionals for vaccination conversations and campaigns.

METHODS

A real-time big data analytics framework was developed using natural language processing sentiment analysis, a form of artificial intelligence. The framework ingests, processes, and analyzes tweets for sentiment and content themes, such as natural health or personal freedom, in real time. A later dataset evaluated the relationship between Twitter sentiment scores and vaccination rates in the United States.

RESULTS

The real-time analytics framework showed a widening gap in sentiment with more negative sentiment after vaccine rollout. After rollout, using a static dataset, an increase in positive sentiment was followed by an increase in vaccination. Lag cross-correlation analysis across US regions showed evidence that once all adults were eligible for vaccination, the sentiment score consistently correlated with vaccination rate with a lag of around 1 week. The Granger causality test further demonstrated that tweet sentiment scores may help predict vaccination rates.

CONCLUSIONS

Social media has influenced the COVID-19 response through valuable information and misinformation and distrust. This tool was used to collect and analyze tweets at scale in real time to study sentiment and key terms of interest. Separate tweet analysis showed that vaccination rates tracked regionally with Twitter vaccine sentiment and might forecast changes in vaccine uptake and/or guide targeted social media and vaccination strategies. Further work is needed to analyze the interplay between specific populations, vaccine sentiment, and vaccination rates.

Co-Design of a Trustworthy AI System in Healthcare: Deep Learning Based Skin Lesion Classifier

This paper documents how an ethically aligned co-design methodology ensures trustworthiness in the early design phase of an artificial intelligence (AI) system component for healthcare. The system explains decisions made by deep learning networks analyzing images of skin lesions. The co-design of trustworthy AI developed here used a holistic approach rather than a static ethical checklist and required a multidisciplinary team of experts working with the AI designers and their managers. Ethical, legal, and technical issues potentially arising from the future use of the AI system were investigated. This paper is a first report on co-designing in the early design phase. Our results can also serve as guidance for other early-phase AI-similar tool developments.

On Assessing Trustworthy AI in Healthcare. Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls

Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and other services that advance population health and wellbeing. However, the use of AI in healthcare also brings potential risks that may cause unintended harm. To guide future developments in AI, the High-Level Expert Group on AI set up by the European Commission (EC), recently published ethics guidelines for what it terms “trustworthy” AI. These guidelines are aimed at a variety of stakeholders, especially guiding practitioners toward more ethical and more robust applications of AI. In line with efforts of the EC, AI ethics scholarship focuses increasingly on converting abstract principles into actionable recommendations. However, the interpretation, relevance, and implementation of trustworthy AI depend on the domain and the context in which the AI system is used. The main contribution of this paper is to demonstrate how to use the general AI HLEG trustworthy AI guidelines in practice in the healthcare domain. To this end, we present a best practice of assessing the use of machine learning as a supportive tool to recognize cardiac arrest in emergency calls. The AI system under assessment is currently in use in the city of Copenhagen in Denmark. The assessment is accomplished by an independent team composed of philosophers, policy makers, social scientists, technical, legal, and medical experts. By leveraging an interdisciplinary team, we aim to expose the complex trade-offs and the necessity for such thorough human review when tackling socio-technical applications of AI in healthcare. For the assessment, we use a process to assess trustworthy AI, called 1Z-Inspection® to identify specific challenges and potential ethical trade-offs when we consider AI in practice.

COVID-19 early-alert signals using human behavior alternative data

Google searches create a window into population-wide thoughts and plans not just of individuals, but populations at large. Since the outbreak of COVID-19 and the non-pharmaceutical interventions introduced to contain it, searches for socially distanced activities have trended. We hypothesize that trends in the volume of search queries related to activities associated with COVID-19 transmission correlate with subsequent COVID-19 caseloads. We present a preliminary analytics framework that examines the relationship between Google search queries and the number of newly confirmed COVID-19 cases in the United States. We designed an experimental tool with search volume indices to track interest in queries related to two themes: isolation and mobility. Our goal was to capture the underlying social dynamics of an unprecedented pandemic using alternative data sources that are new to epidemiology. Our results indicate that the net movement index we defined correlates with COVID-19 weekly new case growth rate with a lag of between 10 and 14 days for the United States at-large, as well as at the state level for 42 out of 50 states with the exception of 8 states (DE, IA, KS, NE, ND, SD, WV, WY) from March to June 2020. In addition, an increasing caseload was seen over the summer in some southern US states. A sharp rise in mobility indices was followed by a sharp increase, respectively, in the case growth data, as seen in our case study of Arizona, California, Florida, and Texas. A sharp decline in mobility indices is often followed by a sharp decline, respectively, in the case growth data, as seen in our case study of Arizona, California, Florida, Texas, and New York. The digital epidemiology framework presented here aims to discover predictors of the pandemic's curve, which could supplement traditional predictive models and inform early warning systems and public health policies.

Comorbidity and clinical factors associated with COVID-19 critical illness and mortality at a large public hospital in New York City in the early phase of the pandemic (March-April 2020)

BACKGROUND

Despite evidence of socio-demographic disparities in outcomes of COVID-19, little is known about characteristics and clinical outcomes of patients admitted to public hospitals during the COVID-19 outbreak.

OBJECTIVE

To assess demographics, comorbid conditions, and clinical factors associated with critical illness and mortality among patients diagnosed with COVID-19 at a public hospital in New York City (NYC) during the first month of the COVID-19 outbreak.

DESIGN

Retrospective chart review of patients diagnosed with COVID-19 admitted to NYC Health + Hospitals / Bellevue Hospital from March 9th to April 8th, 2020.

RESULTS

A total of 337 patients were diagnosed with COVID-19 during the study period. Primary analyses were conducted among those requiring supplemental oxygen (n = 270); half of these patients (135) were admitted to the intensive care unit (ICU). A majority were male (67.4%) and the median age was 58 years. Approximately one-third (32.6%) of hypoxic patients managed outside the ICU required non-rebreather or non-invasive ventilation. Requirement of renal replacement therapy occurred in 42.3% of ICU patients without baseline end-stage renal disease. Overall, 30-day mortality among hypoxic patients was 28.9% (53.3% in the ICU, 4.4% outside the ICU). In adjusted analyses, risk factors associated with mortality included dementia (adjusted risk ratio (aRR) 2.11 95%CI 1.50-2.96), age 65 or older (aRR 1.97, 95%CI 1.31-2.95), obesity (aRR 1.37, 95%CI 1.07-1.74), and male sex (aRR 1.32, 95%CI 1.04-1.70).

CONCLUSION

COVID-19 demonstrated severe morbidity and mortality in critically ill patients. Modifications in care delivery outside the ICU allowed the hospital to effectively care for a surge of critically ill and severely hypoxic patients.

Déjà vu: Stimulating open drug discovery for SARS-CoV-2

In the past decade we have seen two major Ebola virus outbreaks in Africa, the Zika virus in Brazil and the Americas and the current pandemic of coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There is a strong sense of déjà vu because there are still no effective treatments. In the COVID-19 pandemic, despite being a new virus, there are already drugs suggested as active in in vitro assays that are being repurposed in clinical trials. Promising SARS-CoV-2 viral targets and computational approaches are described and discussed. Here, we propose, based on open antiviral drug discovery approaches for previous outbreaks, that there could still be gaps in our approach to drug discovery.

Use of a community-led prevention strategy to enhance behavioral changes towards Ebola virus disease prevention: a qualitative case study in Western Côte d'Ivoire

Background

Starting in December 2013, the Ebola virus disease (EVD) epidemic spread in West Africa through five countries (Sierra Leone, Liberia, Guinea, Nigeria, and Mali), killing over 11,300 people. In partnership with Côte d’Ivoire’s Ministry of Health, the International Rescue Committee instigated a community-led strategy aimed at promoting behavior change in order to prevent potential Ebola outbreaks in the country. The strategy was implemented in Western districts bordering Liberia, Guinea, and Mali. This study aims to analyze the community-led strategy, to document lessons learned from the experience, and to capitalize on the achievements.

Methods

A case study in four districts of Western Côte d’Ivoire, i.e. Biankouma, Danané, Odienné and Touba districts was carried out. Qualitative data in 12 villages (i.e., three villages per district) was collected from 62 healthcare workers, community leaders, and ordinary community members. Data was de-identified, coded and analyzed using a thematic approach.

Results

The community-led strategy was socially accepted in the villages. Even though some community leaders reported that sensitization had been, at times, constrained by a lack of equipment, the people interviewed demonstrated accurate understanding of information about prevention practices. Some practices were easily adopted, while others remained difficult to implement (e.g., ensuring safe and dignified dead body management).

Conclusion

This research demonstrates that sensitization efforts led by well-integrated and respected community leaders can be conducive of behavior change. Lessons learned from the community-led strategy could be applied to future disease outbreaks.

Illustrating and homology modeling the proteins of the Zika virus

The Zika virus (ZIKV) is a flavivirus of the family Flaviviridae, which is similar to dengue virus, yellow fever and West Nile virus. Recent outbreaks in South America, Latin America, the Caribbean and in particular Brazil have led to concern for the spread of the disease and potential to cause Guillain-Barré syndrome and microcephaly. Although ZIKV has been known of for over 60 years there is very little in the way of knowledge of the virus with few publications and no crystal structures. No antivirals have been tested against it either in vitro or in vivo. ZIKV therefore epitomizes a neglected disease. Several suggested steps have been proposed which could be taken to initiate ZIKV antiviral drug discovery using both high throughput screens as well as structure-based design based on homology models for the key proteins. We now describe preliminary homology models created for NS5, FtsJ, NS4B, NS4A, HELICc, DEXDc, peptidase S7, NS2B, NS2A, NS1, E stem, glycoprotein M, propeptide, capsid and glycoprotein E using SWISS-MODEL. Eleven out of 15 models pass our model quality criteria for their further use. While a ZIKV glycoprotein E homology model was initially described in the immature conformation as a trimer, we now describe the mature dimer conformer which allowed the construction of an illustration of the complete virion. By comparing illustrations of ZIKV based on this new homology model and the dengue virus crystal structure we propose potential differences that could be exploited for antiviral and vaccine design. The prediction of sites for glycosylation on this protein may also be useful in this regard. While we await a cryo-EM structure of ZIKV and eventual crystal structures of the individual proteins, these homology models provide the community with a starting point for structure-based design of drugs and vaccines as well as a for computational virtual screening.

Illustrating and homology modeling the proteins of the Zika virus

The Zika virus (ZIKV) is a flavivirus of the family Flaviviridae, which is similar to dengue virus, yellow fever and West Nile virus. Recent outbreaks in South America, Latin America, the Caribbean and in particular Brazil have led to concern for the spread of the disease and potential to cause Guillain-Barré syndrome and microcephaly. Although ZIKV has been known of for over 60 years there is very little in the way of knowledge of the virus with few publications and no crystal structures. No antivirals have been tested against it either in vitro or in vivo. ZIKV therefore epitomizes a neglected disease. Several suggested steps have been proposed which could be taken to initiate ZIKV antiviral drug discovery using both high throughput screens as well as structure-based design based on homology models for the key proteins. We now describe preliminary homology models created for NS5, FtsJ, NS4B, NS4A, HELICc, DEXDc, peptidase S7, NS2B, NS2A, NS1, E stem, glycoprotein M, propeptide, capsid and glycoprotein E using SWISS-MODEL. Eleven out of 15 models pass our model quality criteria for their further use. While a ZIKV glycoprotein E homology model was initially described in the immature conformation as a trimer, we now describe the mature dimer conformer which allowed the construction of an illustration of the complete virion. By comparing illustrations of ZIKV based on this new homology model and the dengue virus crystal structure we propose potential differences that could be exploited for antiviral and vaccine design. The prediction of sites for glycosylation on this protein may also be useful in this regard. While we await a cryo-EM structure of ZIKV and eventual crystal structures of the individual proteins, these homology models provide the community with a starting point for structure-based design of drugs and vaccines as well as a for computational virtual screening.

Open drug discovery for the Zika virus

The Zika virus (ZIKV) outbreak in the Americas has caused global concern that we may be on the brink of a healthcare crisis. The lack of research on ZIKV in the over 60 years that we have known about it has left us with little in the way of starting points for drug discovery. Our response can build on previous efforts with virus outbreaks and lean heavily on work done on other flaviviruses such as dengue virus. We provide some suggestions of what might be possible and propose an open drug discovery effort that mobilizes global science efforts and provides leadership, which thus far has been lacking. We also provide a listing of potential resources and molecules that could be prioritized for testing as in vitro assays for ZIKV are developed. We propose also that in order to incentivize drug discovery, a neglected disease priority review voucher should be available to those who successfully develop an FDA approved treatment. Learning from the response to the ZIKV, the approaches to drug discovery used and the success and failures will be critical for future infectious disease outbreaks.

Prognostic Indicators for Ebola Patient Survival

To determine whether 2 readily available indicators predicted survival among patients with Ebola virus disease in Sierra Leone, we evaluated information for 216 of the 227 patients in Bo District during a 4-month period. The indicators were time from symptom onset to healthcare facility admission and quantitative real-time reverse transcription PCR cycle threshold (Ct), a surrogate for viral load, in first Ebola virus-positive blood sample tested. Of these patients, 151 were alive when detected and had reported healthcare facility admission dates and Ct values available. Time from symptom onset to healthcare facility admission was not associated with survival, but viral load in the first Ebola virus-positive blood sample was inversely associated with survival: 52 (87%) of 60 patients with a Ct of >24 survived and 20 (22%) of 91 with a Ct of <24 survived. Ct values may be useful for clinicians making treatment decisions or managing patient or family expectations.

Finding small molecules for the 'next Ebola'

The current Ebola virus epidemic may provide some suggestions of how we can better prepare for the next pathogen outbreak. We propose several cost effective steps that could be taken that would impact the discovery and use of small molecule therapeutics including: 1. text mine the literature, 2. patent assignees and/or inventors should openly declare their relevant filings, 3. reagents and assays could be commoditized, 4. using manual curation to enhance database links, 5. engage database and curation teams, 6. consider open science approaches, 7. adapt the "box" model for shareable reference compounds, and 8. involve the physician's perspective.

Finding small molecules for the 'next Ebola'

The current Ebola virus epidemic may provide some suggestions of how we can better prepare for the next pathogen outbreak. We propose several cost effective steps that could be taken that would impact the discovery and use of small molecule therapeutics including: 1. text mine the literature, 2. patent assignees and/or inventors should openly declare their relevant filings, 3. reagents and assays could be commoditized, 4. using manual curation to enhance database links, 5. engage database and curation teams, 6. consider open science approaches, 7. adapt the "box" model for shareable reference compounds, and 8. involve the physician's perspective.

FDA approved drugs as potential Ebola treatments

In the search for treatments for the Ebola Virus, multiple screens of FDA drugs have led to the identification of several with promising in vitro activity. These compounds were not originally developed as antivirals and some have been further tested in mouse in vivo models. We put forward the opinion that some of these drugs could be evaluated further and move into the clinic as they are already FDA approved and in many cases readily available. This may be important if there is a further outbreak in future and no other therapeutic is available.

FDA approved drugs as potential Ebola treatments

In the search for treatments for the Ebola Virus, multiple screens of FDA drugs have led to the identification of several with promising in vitro activity. These compounds were not originally developed as antivirals and some have been further tested in mouse in vivo models. We put forward the opinion that some of these drugs could be evaluated further and move into the clinic as they are already FDA approved and in many cases readily available. This may be important if there is a further outbreak in future and no other therapeutic is available.

A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested.

A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested.

Modelling the impact of migration on the HIV epidemic in South Africa

OBJECTIVE

To use observed data to develop a mathematical model that estimates the impact of migration on the spread of HIV in South Africa.

METHODS

A deterministic mathematical model was designed to evaluate the dynamic interactions between mobility, sexual behaviour, HIV, and sexually transmitted infections. The model was based on a population study of 488 adults, which included male migrants, male non-migrants and their rural partners in KwaZulu/Natal, South Africa.

RESULTS

The model predicted that the impact of migration depends upon the epidemic's stage and the pattern of migration. Early in the epidemic, frequent migration between populations with different HIV prevalence rates accelerated HIV spread; however, local sexual risk behaviour determined the eventual scale of the epidemic. If migration is coupled with increased sexual risk behaviour by migrant men, as has been reported in the South African communities studied, HIV prevalence would increase 10 times among migrants' female partners (1.8 to 19%). In contrast, if migration were to occur infrequently, with migration-associated risk behaviour assumed to be at current levels, the predicted epidemic would be one fifth that currently observed (2.8 versus 15.1%).

CONCLUSIONS

Migration primarily influences HIV spread by increasing high-risk sexual behaviour, rather than by connecting areas of low and high risk. Frequent return of migrants is an important risk factor when coupled with increased sexual risk behaviour. Accordingly, intervention programmes in South Africa need to target the sexual behaviour of short-term migrants specifically, even though these individuals may be more difficult to identify.

In vivo radioprotective effects of angiogenic growth factors on the small bowel of C3H mice

This study was undertaken to determine if acidic or basic fibroblast growth factor (FGF1 or FGF2) or vascular endothelial growth factor (VEGF) alters the radiation response of small bowel after total-body irradiation (TBI). Female C3H mice were treated with various doses of angiogenic growth factor administered intravenously 24 h before or 1 h after TBI. Radiation doses ranged from 7 to 18 Gy. End points measured were the number of crypts in three portions of the small bowel, the frequency of apoptosis of crypt cells at various times after TBI, and the LD50/30 (bone marrow syndrome) and LD50/6 (GI syndrome). Fibroblast growth factors alone, without TBI, decreased the number of crypts per circumference significantly. Among the factors tested, FGF2 caused the greatest decline in baseline crypt number. Despite this decrease in the baseline crypt number, after irradiation the number of surviving crypts was greater in animals treated with growth factor. The greatest radioprotection occurred at intermediate doses of growth factor (6 to 18 pg/mouse). Mice treated with FGF1 and FGF2 had crypt survival curves with a slope that was more shallow than that for saline-treated animals, indicating radiation resistance of crypt stem cells in FGF-treated mice. The LD50/6 was increased by approximately 10% for all treatments with angiogenic growth factors, whether given before or after TBI. Apoptosis of crypt cells was maximum at 4 to 8 h after TBI. The cumulative apoptosis was decreased significantly in animals treated with angiogenic growth factors, and the greatest protection against apoptosis was seen in animals treated with FGF2 prior to TBI. All three angiogenic growth factors tested were radioprotective in small bowel whether given 24 h before or 1 h after irradiation. The mechanism of protection is unlikely to involve proliferation of crypt stem cells, but probably does involve prevention of radiation-induced apoptosis or enhanced repair of DNA damage of crypt cells.