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Posts Tagged ‘epidemic

The good, the bad or the ugly? – The relationship between the U.S. and China prior and during Covid-19

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By Julia Lederhofer, PhD

Image by mohamed Hassan from Pixabay 

From a trade war to an increasingly adversarial pandemic response, the U.S. and China find themselves in an increasingly strained diplomatic relationship. With every hurdle — either naturally arising or self-inflicted — both nations’ instinct is to blame the other. Can both countries leave their pride and nationalism behind and foster a spirit of cooperation, or is the world fated for another cold war?

Since the Maoist revolution and China’s embrace of communism in 1949, the two nations have pursued antithetical world orders. Ensuing diplomatic relations ranged from tense standoffs to a complex mix of antagonistic diplomacy, growing rivalry, and economic interdependence. After over half a century, the U.S.-China relationship has evolved into a normalized trade relation – punctuated by then president Bill Clinton signing the U.S.-China Relations Act in October 2000. In 2001, China joined the World Trade Organization. By 2010, China was the world’s second largest economy. It trailed only the US, and economic forecasts predicted even the unequaled American economy would be surpassed by 2027. Unsurprisingly, tensions between China and the West arose.

In 2012 the U.S., EU and Japan filed a request for consultations with China at the World Trade Organization because of their restrictions on exporting earth metals. They stated that China violated international trade norms. In the following years, then U.S. President Barack Obama and the Chinese President Xi Jinping agreed on establishing a new type of relationship for the U.S. and China. Their aim was to ease the U.S./China tense relationship by solving bilateral, regional and global issues in a friendly manner. In 2017, the U.S. Commerce Secretary Wilbur Ross unveiled a ten-part agreement between Beijing and Washington, which contained the expansion of trade products like beef, poultry and electronic payments. However, the countries did not address other trade issues that were still unresolved from the Barack Obama era, like aluminum, steel or car parts. In 2018, President Donald Trump changed course from his predecessor by announcing extensive tariffs on Chinese imports, which lead to a U.S.-China Trade War escalation. Fast forward to May 2019, the Trump administration continued to sweep tariffs from 10 to 25 percent on $200 billion worth of Chinese goods. China reciprocated by increasing tariffs on $60 billion worth of American goods. Days after the heated discussion, the Trump administration banned U.S. companies from using foreign-made telecommunications equipment, as they believe that they could threaten national security. Many think that this was a move to target Huawei. Moreover, Huawei was added to the foreign entity blacklist by the U.S. Commerce Department. Tensions between the U.S. and China continued, but early in January 2020, President Trump and the Chinese Vice Premier Liu He signed the ‘Phase One’ Trade Deal agreement, a final breakthrough in the almost two year trade war between the two big fish. The deal lowered, amongst other things, some of the U.S. tariffs on Chinese imports and commits China to buying an additional $200 billion worth of American goods over the next two years. The years-long trade war that threatened the entire global economy finally had an end in sight. The positive undercurrent of two once again friendly superpowers, however, would be short lived. The world quickly entered a new economic, and health, crisis – the COVID-19 Pandemic. 

Beginning in the Chinese city of Wuhan in December 2019, the novel coronavirus quickly spread, leading the World Health Organization (WHO) to declare a global pandemic in March (11th, 2020). China and the U.S. were quick to blame each other as the pandemic worsened. China leveled the claim that the U.S. military brought the virus to China, while President Trump accused China of not reporting the “Chinese virus” earlier, therefore failing to prevent the pandemic. The Trump administration turned its ire towards the WHO. The Trump administration cut funding and alleged the international organization showed bias towards China. By April, the drama ventured into the absurd. The Trump administration reported that they have evidence that the Coronavirus was human made in a Chinese laboratory and purposely released. In response, Beijing published an article denying everything from claims that they under-reported case numbers, to allegations the virus spread from eating bats. In China’s eyes, they were merely the first to suffer from the virus. China portrays itself as a model in how to combat the virus and offers the world a source of medical equipment. Whether any of the political grandstanding by either side has convinced their own citizens, let alone the outside world, remains to be seen. Outside of their respective homelands both countries’ claims fall on deaf ears. The general consensus holds China responsible for mishandling the early stages of the outbreak, as well as outright denials, withholdings and cover-ups. The U.S.’s claim that the virus was produced in a lab has been repeatedly debunked, and the move to cut WHO funding has been met with widespread criticism. 

The coronavirus has pushed the U.S.-China relationship, the most important world’s powerful economic relationship, to a precipice, with the ‘Phase One’ Trade Deal agreement dangling over the edge. The mudslinging over the origins of the coronavirus will not help and will only distract from the challenging health crisis, which is coupled with the biggest hit to the global economy since the Great Depression. Both China and the U.S. cannot risk any further destabilization of their economies and must look to rebuild trust. The first major test could come as early as December 2022. Under the Phase One agreement, China is committed to buying $200 billion additional goods and services on agriculture, energy and manufacturing. Due to the pandemic, China will almost certainly miss this target by December 2022. The U.S.’s response will dictate the future. Time will tell if both countries’ leaders are willing to end the blame game and begin to restore trust. The truth of the early days of the pandemic outbreak may never be known, but one can only hope that both political leaders will be able to forget their conflicts for the name of peace and prosperity for the whole world.

Written by sciencepolicyforall

May 29, 2020 at 10:13 am

The Use of COVID-19 Prediction Models in Guiding Policy Decisions

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By Amanda Perofsky, PhD

Image by Arek Socha from Pixabay 

Models are essential tools for estimating biological aspects of pathogens, how diseases will spread, and the impacts of policies and interventions. Indeed, there is a two-decade history of utilizing mathematical and computational approaches for public health, particularly for preventing and controlling outbreaks of emerging pathogens and informing intervention strategies (Viboud et al. 2018). Recent examples include the 2009 H1N1 influenza pandemic and the MERS (2014-2016), Ebola (Western Africa: 2014-2016; Democratic Republic of Congo: 2018-present), and Zika (2015-2016) epidemics. Since the 2009 H1N1 pandemic, government agencies have organized infectious disease challenges to formally engage the disease modeling community and improve forecasting performance for both endemic and emerging pathogens, such as seasonal influenzadenguechikungunya, and Ebola. Soon after the novel coronavirus SARS-CoV-2 emerged in Wuhan, China in late 2019, researchers participating in the US Centers for Disease Control and Prevention’s annual challenge to predict seasonal flu activity mobilized to produce short-term forecasts of COVID-19 deaths for the United States. 

Mathematical and computational approaches are especially critical during the coronavirus disease 2019 (COVID-19) pandemic, due to uncertainties regarding biological and immunological aspects of SARS-CoV-2 infection, the logistical hurdles in accurately estimating COVID-19 infectionsprevalence, and mortality in communities, and the immense health, economic, and societal impacts of the pandemic. As a consequence, the COVID-19 pandemic has sparked efforts by numerous research groups to forecast cases, hospitalizations, and deaths and predict how public health interventions will alter epidemic trajectories. These models have significant policy implications as decision makers in government, public health, and health care seek to swiftly minimize cases and deaths, allocate limited medical resources, avoid hospital surges, and mitigate the socioeconomic upheaval caused by the pandemic. 

Models are inherently simplified versions of complex biological, epidemiological, and social processes and can vary widely in terms of methodologies, assumptions, uncertainties, conclusions, and policy recommendations. Various COVID-19 prediction models aim to capture epidemic dynamics from a global scale down to the resolution of countries, states, counties, or cities and are used to inform decision making on a range of time horizons, from days to weeks to months. 

The three main modeling and computational approaches for predicting COVID-19 epidemic dynamics include: 

1. SIR/SEIR compartmental models sort individuals into susceptible (S), exposed (E), infected (I), and recovered (R) compartments and use differential equations to dictate how individuals move through these compartments. Given the epidemiologic and virologic evidence for SARS-CoV-2 transmission from asymptomatic and pre-symptomatic people (Furukawa et al. 2020), many COVID-19 SIR/SEIR models subdivide the infected compartment into asymptomatic and symptomatic individuals. Hospitalized, ICU, and death compartments are also typically incorporated, as these are the main indicators that inform COVID-19 public health decisions. For example, researchers at Columbia University have built a metapopulation SEIR model to simulate COVID-19 transmission within and among US counties and to make daily and short-term projections of incidence, hospitalizations, and deaths. 

Modelers make assumptions concerning the number of individuals that initially fall into each compartment and the rate of flow between compartments. These flows are governed by different parameters, such as the period of time it takes one infected person to infect another person (“the serial interval”), contact rates between individuals, the average number of infections caused by one infected person (“the basic reproduction number” or “R0”), the rates at which different demographic groups recover and die, and whether protective immunity after recovery is long-lasting or waning. The values for several of these parameters were unknown at the beginning of the COVID-19 pandemic and remain difficult to quantify until we have more comprehensive surveillance data and knowledge concerning the SARS-CoV-2 transmission process. For example, the relative incidence of asymptomatic to symptomatic infections and whether asymptomatic infection confers protective immunity continue to be key uncertainties and affect the number of tests required for testing-based interventions. To minimize the impact of incomplete data and erroneous assumptions, modelers typically perform sensitivity analyses, in which they tweak initial conditions and parameter values across several model runs.

2. Agent-based models  (ABMs) use real-world data to create synthetic populations of individual “agents” (i.e., people) with realistic spatial and sociodemographic characteristics and then simulate disease spread in these populations over discrete time steps. Agent-based models examine the role of individual-level processes in generating population-level dynamics and are useful for modeling counterfactual outcomes in the face of complexity (Marshal and Galea 2015). However, like SIR/SEIR models, they are reliant on assumptions concerning the infection process and the timing and effectiveness of different interventions and policies, such as social distancing and stay-at-home measures. The Institute for Disease Modeling’s Covasim (COVID-19 Agent-based Simulator) incorporates age structure and population size, transmission networks in households, schools, workplaces, and communities, age-specific disease outcomes, and within-host viral dynamics to project cases and peak hospital demand. Northeastern University’s Global Epidemic and Mobility Model (GLEAM) is a hybrid SIR-ABM model that simulates 3200 subpopulations worldwide, and mobility between these subpopulations, to describe and project the spread of COVID-19 in the United States.

3. Curve-fitting/extrapolation models such as the Institute for Health Metrics and Evaluation (IHME) model, are statistical models that do not model the person-to-person disease transmission process itself. For example, the IHME model uses reported deaths for countries outside of the US where the COVID-19 pandemic has already hit. It then examines where the US falls on that mortality curve and applies statistical approximations to forecast future death counts, assuming that systematic variation across locations is due to the timing of social distancing measures and that other differences are explained by random effects. Unlike SIR/SEIR models and ABMs, statistical models are not reliant on difficult-to-estimate epidemiological parameters, such as R0. However, because they can only estimate the initial wave of cases, statistical approaches are not suitable for projecting longer-term epidemiological dynamics. Despite criticism from the scientific community concerning the validity of the curve-fitting/extrapolation approach for long-term projections and IHME’s forecaststhe White House has relied on the IHME model as a national guide for projecting peaks in deaths and hospital demands

Given the sparsity of data on SARS-CoV-2 transmission, the effectiveness of different public health interventions, and population behavior once interventions are relaxed, there are broad uncertainty bands in model projections, and even models with similar objectives and methodologies can produce disparate estimates. Some forecasting models assume existing interventions and population behavior will continue through the projected period whereas others make assumptions concerning how interventions and social distancing will change in the future. Thus, it is important for decision makers to not rely on a single model for projections and to understand the key assumptions underlying each model. Nicholas Reich, a biostatistician at University of Massachusetts Amherst, and colleagues have recently combined sixteen mortality forecasts from different disease modeling groups to produce national “ensemble” forecasts for one to four-week horizonswhich are released weekly by the CDC. Reich plans to start evaluating the accuracy of individual models so that more accurate models are weighted more heavily in ensemble projections. Though estimates for national models are now converging due to increasing data availability and an overall decrease in daily COVID-19 cases across locations, forecasts will likely diverge again in the coming weeks as social distancing measures are relaxed in many US states

Katriona Shea, a theoretical ecologist at Penn State University, and colleagues advocate a systematic approach beyond ensemble forecasts, in which contributions from multiple groups are leveraged to support decision making (Shea et al. 2020). Shea and colleagues’ proposed process entails applying formal expert elicitation methods to generate and synthesize ideas across multiple models and to share important insights among research groups. A decision theoretic framework is applied to account for uncertainties within and between models and to achieve well-defined policy objectives. Their research team was recently awarded a Grant for Rapid Response Research (RAPID) from the National Science Foundation to immediately implement this process to inform COVID-19 policy. By utilizing the many research groups already producing forecasts, this strategy should be straightforward to implement and produce more robust results from the existing process of CDC’s COVID-19 forecasting collaboration. 

The dynamic circumstances surrounding the COVID-19 pandemic and “patchwork” of highly-localized outbreaks and government responses make it difficult for modelers to produce forecasts beyond a few weeks. Thus, there is a less coordinated effort to predict longer-term epidemiological dynamics. While the COVID-19 pandemic has increased interactions between modelers and decision makers, these interactions can be tense and difficult because social distancing measures are economically costly and policy decisions are not based solely on public health outcomes. Despite these challenges, models are essential for addressing questions related to disease spread and resource management. As the pandemic progresses, models should also play fundamental roles in supporting decisions related to triggering and relaxing social distancing and lockdown measures, the delivery of widespread testing, clinical trial designs, and vaccination strategies (Currie et al. 2020). 

Written by sciencepolicyforall

May 22, 2020 at 12:38 pm

Effect of Travel Ban on Spread of Viral Outbreak

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By Olive Jung PhD

Image by Gerd Altmann from Pixabay 

In recent weeks, governments around the world have been addressing the spread of Coronavirus (known formally as COVID-19) through travel restrictions and/or outright ban. These travel policies have brought the validity of the travel ban – whether it is an effective measure to prevent viral spread – back onto the surface of mainstream media debate.  United States’ travel policies have been in effect since February 2, 2020.  Despite the implementation of these restrictions, the virus has shown no signs of slowing since dozen cases were first confirmed in Wuhan, China on December 31, 2019

As the world becomes more interconnected, travel restrictions have become increasingly difficult to implement. The World Health Organization (WHO) has run numerous simulations as well as past case studies to understand how travel restrictions impacted the rate at which viruses spread. Contrary to the popular misconception, the ban itself has minimal to no effect because the ban itself is not a complete measure to stop all trans-continental, trans-national movements of persons. According to simulations by the WHO, even when restricting air travel by 95% it would hypothetically only delay the arrival of virus into the United States from Sydney or Hong Kong by 2-3 weeks. FAA lists that the agency typically handle 44,000 flights per da, including intercontinental flights. Restricting 95% would mean stopping entry of 41,800 flights.  This scenario was calculated based on not just a specific restriction from flights out of the epicenter of the outbreak, but on total, existing flight routesA total ban on all flights would still not effectively stem the spread of viral cases. Even this “case-scenario” measurement is unrealistic and itself would bring a whole slew of ethical, socioeconomical impacts that may not have yet been evaluated in the real world. 

Unfortunately, strict travel restrictions may have more harms than benefits. When Princess Diamond, a cruise ship near Japan, confirmed positive cases of COVID-19, the immediate response was to quarantine and restrict the movement of the passengers on the ship. Not only did jeopardizes the patients’ access to treatment, it perpetuated fear amongst other passengers as there was no decision-making transparency or clear communication/directives about the situation relayed between government agencies and their respective nationals. Dr. Kentaro Iwata, an infectious disease specialist at Kobe University, slammed the conditions on the cruise ship, arguing it they lacked the supplies and equipment necessary to deal with COVID-19. Not only was there no distinction between the infection-free zone and the infection zone, but the environment was completely chaotic and individuals were moving around the entirety of the ship without personal protective equipment (PPE). This led to upward tick of COVID-19 cases that could have been prevented through proper quarantine and isolation measures of positive cases.

What is more effective in stemming such viral outbreaks is for the governments to be transparent about the spread.  It provides public assurance and confidence that the government is committed to communicating risk and situational assessment regarding the outbreak. Further, they need to provide more clear-cut policies for travelers originating from or near outbreak areas so that they also know to self-quarantine and encourage the public to follow good nonpharmaceutical interventions, such as avoiding large crowds, handwashing, staggering shifts at workplaces to decrease rush hour commuter traffic. The government needs to focus on ways to effectively:

  • Measure the responses of travelers who may have travelled to high-risk area so that they can reach out and coordinate with those affected to minimize further public contact,
  • Monitor at-risk individuals and relay risk communications to the general public,
  • Provide streamlined guidelines and assistance for hospitals conducting testing and providing medical/healthcare intervention
  • Focus on mitigation of the viral outbreak and reduce susceptibility of uninfected patients (ex: vaccines). 

Given the current rate of outbreak, withstanding travel restrictions must be re-evaluated because it will potentially (1) bring in unintended consequences, (2) encourage misguided assumptions about the virus and its mode of transmission, (3) enforce incorrect and damaging racial stereotypes, especially when the origins of the virus is linked to a specific geographical region. Instead, as evidence shows, governments should focus on prevention – by consistently providing funding to scientists working in infectious diseases even when there is no viral outbreak – and mitigation of cases – by allowing the scientific experts to plan and execute public health policies to contain the infection. By providing transparent updates on confirmed cases, effectively maintaining quarantines, monitoring at-risk individuals, and following evidence-based medical and health care practices, the outcomes on the cruise ship could have been much different and would not have had to require the further, riskier intervention that was undertaken by the State Department (decision which was not supported by CDC).

Hopefully, based on the past lessons learnt as well as taking heed of global health and infectious disease experts, the governments involved can remedy some, if not all, of the current policies regarding COVID-19 that are negatively impacting patients, their families, and the general public. 

Written by sciencepolicyforall

March 1, 2020 at 10:09 pm

Science Policy Around the Web February 20th, 2020

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By Somayeh Hooshmand, PhD

Image by skeeze from Pixabay 

Researchers Identify States Where Improved Sun Protection Could Prevent the Most Melanomas

Rates of new cancer diagnoses continue to increase in the US, and skin cancer is one of the most common. Although many skin cancer cases can be prevented, it greatly affects quality of life, making it a major public health concern. According to a recent study, 91% of all melanomas in the US are caused by too much exposure to ultraviolet (UV) radiation from the sun. However, the rates vary among populations, and are as high as 94% among non-Hispanic whites. This study focused on the non-Hispanic white population at the state level that exhibit higher levels of melanoma and suggested sun protection measures across the states.

While incidence rates for melanoma as a result of exposure to the UV radiation was noticeably high in all states, the District of Columbia had the lowest proportion of melanoma among non‐Hispanic whites —87.6% of all cases and Hawaii had the highest, with 97.3%  of all cases. 

How to protect yourself from UV radiation:

The risk of skin damage increases when you stay in the sun for a long time, especially with a high UV Index and without sufficient sun protection. Dr. Farhad Islami, MD, PhD, said that “The amount of UV exposure you get depends on both the strength of the sun’s rays—measured by the UV Index—and the length of the time your skin is exposed to it”. He said “You can’t change the UV Index, but you can change how long you’re outside and how you protect your skin”. 

You should use sunscreen with a sun protection factor (SPF) of 15 or higher and limit the amount of time you’re in the sun, avoid peak sunlight, wear sunglasses and try to reduce indoor tanning. The authors hope that state- and community-level cancer control programs will result in school-based programs and indoor tanning regulations based on this research findings.

(Amy Maxmem, Nature)

‘Ghost’ DNA In West Africans Complicates Story of Human Origins

The genetic history of people in present-day West Africa indicates an earlier episode of breeding between different groups, leading to introgression of genetic material into modern humans. 

The recent research in human genetics by Sankararaman et al. found “ghost DNA” by analyzing the genomes of 405 West Africans, and suggests that about 50,000 years ago, ancient human procreated with another group of ancient humans or unknown ancestors that scientists so far did not know existed. The understanding so far has been that Homo sapiens, our own species lived alongside other groups that split off at different times from the same genetic family tree. There exists abundant evidence from other parts of the world that early humans had sex with other groups, like Neanderthals (found in people of European and Asian descent today) and Denisovans (found in people from Oceania). They state that the found unusual DNA came from a yet-to-be-discovered group, as it isn’t associated with either Neanderthals or Denisovans. The lack of knowledge about this group led the researchers to term it ‘ghost’ DNA. They think that this occurred due to interbreeding (single event or over an extended period of time) around the same time when Neanderthals were breeding with modern humans elsewhere in the world.

Their findings appear in the journal Science Advances, but there are still many questions about  ‘Ghost’ DNA that remain unanswered. As Sankararaman says, “Are they just randomly floating in our genomes? Do they have any kind of adaptive benefits? Do they have deleterious consequences? Those are all questions which would be fantastic to start thinking about.”

(Merrit Kennedy, NPR)

Written by sciencepolicyforall

February 20, 2020 at 4:28 pm

Science Policy Around the Web February 18th, 2020

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By Silvia Preite, PhD

Image by Konstantin Kolosov from Pixabay 

How science is fighting the new Coronavirus disease 2019 (COVID-19)

The increase in new infections of the novel coronavirus, recently named SARS-CoV-2, COVID-19), is being tightly monitored by the WHO (World Health Organization). Currently there are 71,429 confirmed world-wide cases, and 1772 deaths in China. Scientists around the world are making extensive efforts to fight COVID-19 in multiple ways: 1) utilizing epidemiology to understand how and why the virus is spreading; 2) studying the genetic composition of the virus to learn how it works, survives and spreads across species; 3) conducing biomedical research to find and test effective therapeutics. The development of novel drugs is generally a slow process, usually taking several years to be completed. Therefore, with the urgency of the current epidemic, specific vaccine development and identification and production of viral neutralizing antibodies do not seem useful immediate solutions. 

The scientific community is mainly directing its attention toward the exploration of already developed drugs, such as antivirals, stem cells, and Chinese traditional medicines. Examples of these drugs are an HIV-drug cocktail (lopinavir and ritonavir) and an experimental antiviral called remdesivir. Both options have shown initial promise in animal models infected by related strains of coronaviruses. Other tested treatment includes a malaria drug (chloroquine) and steroids, respectively aimed at killing the virus and reducing inflammation.

Overall, China is currently launching more than 80 clinical trials to test treatments for this coronavirus. To ensure high quality and public trust in the outcomes of these trials, the WHO is working closely with Chinese scientists and authorities to set standards to design, execute, and analyze these studies properly. 

Failing to control the infection could result in the virus becoming endemic, like seasonal influenza infection. Sharing of research results at global levels and adequately designed clinical trials are two essential elements that the medical and scientific community is currently adopting to properly fight the infection. Meanwhile, basic and translational research all over the world is moving forward to search for new drugs that would be useful in the future to combat multiple coronaviruses, including the ones that we haven’t faced yet. 

Written by sciencepolicyforall

February 18, 2020 at 3:57 pm

Science Policy Around the Web January 28th, 2020

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By Hannah King PhD

Source: Flickr

Containing new coronavirus may not be feasible, experts say, as they warn of possible sustained global spread

The Wuhan Coronavirus has come to American soil, with 5 cases identified throughout the U.S. on top of the more than 2,000 cases confirmed and 82 deaths in China. These infections have put a spotlight on the strategies that government and public health organizations put in place to limit the spread of novel infectious diseases, the successes these measures can achieve and the impossibility of ever being fully prepared.

Chinese authorities have put strict measures into place to try to contain the outbreak, including postponing the return to work following the Chinese Lunar New Year Holiday across China, and preventing transport—flights, trains, buses and cars—from leaving Wuhan, the most affected provence.

Other countries, including the US, have also put screening measures into place. At-risk airports have implemented temperature screens, and hospitals are on high alert and rapidly adapting their screening procedures to identify individuals suspected of carrying the disease. This has resulted in prompt identification of cases in the US and patients have been isolated prior to confirmation of infection. According to health officials the reactions to these cases have been an “example of how it should be done”.

The global scientific effort has also been praised. The virus was described less than a month after cases were first reported, and the first scientific papers have already been released. A comment in the journal The Lancet by epidemiologist David Heymann also praised the rapid peer review and free sharing of information which has enabled a “global collaboration” to better understand and prevent transmission of this disease.

This containment has resulted in the World Heath Organisation opting on Thursday to not declare this disease a Public Health Emergency of International Concern (PHEIC). This largely reflects the relatively small scale of spread outside of China, including no reported cases of transmission. According to Didier Houssin, the chair of the WHO emergency committee assessing the Wuhan Coronavirus, it is also due to “the efforts presently made by Chinese authorities in order to contain the disease.”

However, experts are warning that this may be insufficient to prevent spread of this disease. Dr. Allison McGeer, an infectious disease specialist from Toronto, has suggested that “the more we learn about it, the greater the possibility is that transmission will not be able to be controlled with public health measures”. Professor Neil Ferguson, a public health expert from Imperial College, London, suggested that there may already be as many as 100,000 cases in China

The virus also has properties that may make containment more of a challenge. It has a shorter incubation period than other coronaviruses such as SARS, making it more difficult to track potentially infected persons before they can potentially infect others. It has also emerged that the virus may not cause symptoms in all infected individuals. It is still unclear whether asymptomatic individuals are able to transmit the virus, however if this were possible the effectiveness of public heath tools such as quarantine and isolation to stop viral spread would be greatly reduced.

A further concern in the US is the need for samples in the US to be tested for the coronavirus by the CDC. Kelly Wroblewski, from the American Public Health Laboratories, has sad that if the virus started to spread widely in the US this may “overwhelm” a single testing location, and recommended decentralizing this process.

While many containment policies have been enacted here, experts such as Dr. Trevor Bedford, a computational biologist at the Fred Hutchinson Cancer Research Center, cautions that with the current infection rate of the new virus “if it’s not contained shortly, I think we are looking at a pandemic”.

(Helen Branswell, Stat News

Written by sciencepolicyforall

January 28, 2020 at 4:43 pm

Science Policy Around the Web November 5th, 2019

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By Silvia Preite

Source: Flickr

Natural measles infection impairs the preexisting immunity to other pathogens

Measles is one of the most contagious human infectious disease, causing over 100,000 deaths worldwide every year. Despite the availability of a safe and effective vaccine, the number of new measles cases is growing fast, with a 30% global increase between 2017 and 2018. Misguided vaccine safety concerns are leading to under-vaccination that, together with extensive international travels of people around the world, contributes to this sharp increase in measles cases. As October 2019, there are more than 1250 confirmed cases of measles in the U.S. alone – the highest number reported since 1992. 

The harmful consequences of a Measles infection go beyond the infection with the virus itself. Epidemiological studies have associated measles outbreaks with increased morbidity and mortality to secondary unrelated reasons. Two recent studies published in Science Immunology and Science shed lights on this phenomenon: the authors showed that measles suppress the body’s immune system, reducing the ability to respond to other infections. 

Scientists analyzed a cohort of children from an Orthodox Protestant community in the Netherlands that have been not vaccinated by their parents for religious reasons. A total of seventy-seven of these children partook in the study before and after a measles outbreak in 2013. The blood of children pre-measles contraction contained antibodies (proteins produced by immune cells called B cells) that protect against common pathogens. However, after a natural measles infection, between 20 and 70% of these antibodies were lost. The immune system becomes “ignorant” again to viruses that it had encountered in the past. This “amnesia” of the immune system increases the risk of infections and slows down the ability of our immune system to fight pathogens such as influenza. 

Strikingly, children receiving vaccination against measles did not display such suppression of acquired immunity. These data further support the importance of widespread vaccination strategies to protect against measles but also to maintain a proper herd immunity to other pathogens.

(Petrova et al., Science Immunology, 2019 AND Mina et al., Science, 2019)

Written by sciencepolicyforall

November 5, 2019 at 4:27 pm

Science Policy Around the Web September 13th, 2019

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By Neetu M. Gulati PhD

Image by mika mamy from Pixabay 

Genetically modified mosquitoes breed in Brazil

An experiment to curb the population of tropical disease-carrying mosquitoes in Brazil may have failed. In 2013 and 2015, mosquitoes with a modification called OX513A, which prevents these mosquitoes from reaching adulthood and being able to reproduce, were released into a region of Brazil. This experiment was meant to limit the spread of mosquito-borne infectious diseases that plague the area, including zika, dengue, and yellow fever. 

Initially, the goal of the genetic modification experiment was to reduce the mosquito population by 90%, which was successful during the field trial. Only about 4% of genetically modified mosquitoes were expected to be able to reach adulthood, and it was hypothesized that these mosquitoes would be too weak to reproduce. However, about 18 months after the experimental trial period ended, the mosquito population has returned to pre-trial levels. A recent study has revealed that the gene modification has been passed on in 10-60% of the mosquitoes in the area, suggesting they were able to reproduce. Furthermore, modified mosquitoes are as able to carry infectious diseases as non-modified mosquitoes. Critics of the experiment warn that not enough was known about these mosquitoes and there may be unintended consequences to the genetic modification, including a possibility of making the species more robust. The authors of the new study posited “These results demonstrate the importance of having in place a genetic monitoring program during releases of transgenic organisms to detect unanticipated consequences.”

(Fabian Schmidt, Deutsche Welle

America is in danger of losing its “measles-free” status

In 2000 the United States was declared measles-free, 37 years after the introduction of the measles vaccine in the US and Canada. Now, almost two decades later, the US is at risk of losing an official designation of “measles-elimination” status in October. This status is only given to countries without continuous measles transmission for at least one year, where cases of the disease can be linked back to a traveler who brought the virus from another place where it has been circulating. An outbreak of measles in New York state now jeopardizes this. The CDC reported over 1,200 measles cases in the US, with over 75% of the cases occurring in the state of New York. 

This is occurring because it is common in some groups to opt out of the measles vaccine. And it is not just the US; measles cases have increased around the world, and some other countries have also lost measles-free status in the last year.

The outbreak in New York can be traced back to Ukraine, which has had tens of thousands of measles cases in the last year. It then spread throughout a tight-knit community of people who chose not to vaccinate for perceived safety concerns. So while this outbreak can be linked to a traveler, many are concerned that if vaccine coverage rates continue to decline, the virus could spread enough, especially in under-vaccinated communities, that the outbreaks will begin to be “homegrown.”

(Julia Belluz, Vox)

Written by sciencepolicyforall

September 13, 2019 at 10:53 am

Science Policy Around the Web August 20th, 2019

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By Mohor Sengupta PhD

Image by Ryan McGuire from Pixabay 

FDA makes new push for graphic warning labels on cigarettes

According to government records, the percentage of smokers in the U.S. has reduced from 40% of the population in the 1960’s to 14%. Despite this dramatic decrease, approximately 480,000 people in the U.S. die each year from diseases directly related to smoking. In an attempt to educate smokers about the dangerous medical consequences of smoking, in 2009 the FDA proposed 9 graphic labels to be printed on cigarette packets. However the FDA’s plan didn’t see the light of day when five tobacco companies challenged the FDA’s decision in court and in 2012 won on grounds of free speech. The judges who ruled in favor of the tobacco companies said that “[the images were] crafted to evoke a strong emotional response,” rather than educating consumers. 

The FDA then backed out saying that it will work on introducing new images and it was soon to announce new proposed labels. In 2016, a lawsuit was filed by health groups against the FDA for not proposing a new plan soon enough. Last Thursday, the FDA announced 13 new graphic labels to be displayed on cigarette packets that would show cancerous tumors, diseased lungs, and feet with amputated toes. The FDA’s tobacco director Mitch Zeller said that these new labels had been designed while keeping in mind the limited public awareness of lesser-known diseases caused by smoking. 

For 35 years, everything that the USA’s cigarette packets have told consumers about the harmfulness of smoking has been contained in a warning statement so tiny that it is missed by most consumers. Research has shown that graphic label inclusion on cigarette packets discourages smokers, and Canada was the first country to adopt this measure in 2000. 

Since then, more data have come to light identifying graphic images as an effect anti-smoking measure. A 2013 study showed that participants tended to respond to graphic labels rather than warning statements on cigarette packets. Another 2013 study estimated that if the FDA had adopted graphic labels in 2012, 5.3 to 8.6 million adults would have quit smoking in a year. They based their results on similar data from Canada where graphic labels are in use. 

It is anticipated that Big Tobacco will challenge the FDA’s move once again. Some of them are already citing the First Amendment as their defense. It is now time to see what is decided if the matter is taken to the courts once again. While thousands of people continue to die because of smoking habits in the USA, and graphic label inclusion on cigarette packets are repeatedly challenged by the tobacco industry, nearly 120 countries across the world have already adopted this measure and are reaping its benefits. 

(Matthew Perrone, STAT)

Experimental Ebola Drugs Saved Lives In Congo Outbreak

Ebola is raging in the Democratic Republic of Congo (DRC). However, a climate of distrust around Ebola clinics compounded with political upheavals in DRC has discouraged patients in the early stages of infection from leaving their community and seeking help in designated Ebola clinics. In this way, the virus has rapidly spread across communities and now threatens people outside of DRC as well. 

Despite these issues, efforts are underway to combat Ebola and develop more effective treatment strategies. A NIAID-funded study that compared four drugs against the Ebola virus recently concluded that two of them showed better results in combating the disease. The study, called ‘Pamoja Tulinde Maisha’ (PALM), is a randomized controlled trial of the four drugs and started on November 2018 as part of the emergency response in DRC.

The four investigational agents were Remdesivir, a commonly used antiviral drug, ZMapp, which showed effectiveness in previous Ebola outbreaks, REGN-EB3, developed by Regeneron and mAb114, a monoclonal antibody jointly developed by NIAID and INRB (in the DRC). 

Having reached a definite conclusion about the effectiveness of the four drugs, the PALM trial stopped earlier than originally scheduled. Preliminary results released on August 9, 2019 show only 30% of Ebola Virus Disease (EVD) patients treated with REGN-EB3 or mAb114 succumbed to the infection, compared to half of those treated with ZMapp or Remdesivir. When analysis was restricted to the relatively healthier patients receiving the more potent treatments, 6% and 11% died on REGN-EB3 and mAb114 treatment regimes respectively. 

With these preliminary results, patients on Remdesivir and ZMapp will now be switched to one of the more effective drugs based on their physician’s discretion. The study will continue to measure the effects of the two drugs from now on. The final analysis of the study data is likely to be made available later this year. 

(Richard Harris, NPR)


Written by sciencepolicyforall

August 20, 2019 at 4:56 pm

Science Policy Around the Web – July 12th, 2019

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By Mohor Sengupta, Ph.D.

Source: Maxpixel

CDC made a synthetic Ebola virus to test treatments. It worked

During the 2014-2016 Ebola outbreak in Guinea, West Africa, infectious samples containing the virus were shared by local government with international scientific communities. Using these materials, Dr. Gary Kobinger and his team developed and tested the efficacy of a monoclonal antibody vaccine at the Canadian National Laboratory. The same vaccine, ZMapp, and other therapies are currently being deployed in the most recent Ebola outbreak, which is the second largest outbreak so far. Beginning in ] 2018 in the Democratic Republic of Congo (DRC), this outbreak is still on the roll. Unfortunately, the Centers of Disease Control and Prevention (CDC) did not have any viral samples this time, meaning they were unable to test the efficacy of ZMapp and other drugs against the recent viral strain. 

Scientists at the CDC, led by Dr. Laura McMullan, constructed an artificial virus from the sequence of the current strain shared by DRC’s National Biomedical Research Institute (INRB). The group used the sequence data to perform reverse genetics and generate the authentic Ebola virus that’s currently infecting scores of people in Ituri and North Kivu provinces of DRC. 

“It takes a lot of resources and a lot of money and a lot of energy to make a cloned virus by reverse genetics. And it would be so much easier if somebody had just sent the isolate”, Dr. Thomas Geisbert, who is not involved in the work, said. 

The CDC group established the efficacy of current treatments (a drug called Remdesivir and the vaccine ZMapp) on the viral strain by using their artificial virus for all the tests. Their work was published Tuesday in the journal Lancet.

For all four Ebola outbreaks that the DRC has seen, healthcare authorities have not shared viral specimens with foreign Ebola researchers. Instead, the whole genome sequence was provided every time. With the whole genome sequence data, the Lancet paper noted that there are at least two Ebola strains in DRC that have independently crossed into the human population.  

Reasons for not sharing viral samples by DRC are not known but it is a roadblock to rapid and efficient treatments in affected geographical regions. McMullan said that shipping of samples across such large distances is often a logistical issue and requires permission from several authorities and coordination of many people. 

 (Helen Branswell, STAT)

Plastic Has A Big Carbon Footprint — But That Isn’t The Whole Story

We are all too familiar with ghastly images of dead whales with plastic-filled stomachs. These images are compounded by pictures of how much waste is generated, such as a picture of a twenty-story high mound of plastic trash in a developing country that appeared in a recent news article. While there is worldwide concern about how to eliminate use of plastics, there is very little discussion about the environmental impact of the materials that will replace plastic. 

Plastic has a high carbon footprint. In a recent report the Center for International Environmental Law (CIEL) has broken down the individual steps of greenhouse gas production, from the beginning of plastic production until it ends up incinerated as a waste. Manufactured from oil and natural gas, plastic production adds to carbon footprint right from its cradle when gases and oils leak into the environment. Subsequently, delivery of raw materials to the production sites further add to the burden. Being among the most energy intensive materials to produce, plastic production takes a heavy toll on energy, water and electricity. Finally, when plastics are incinerated, greenhouse gases end up in the environment. 

But what about the materials that commonly substitute for plastic, such as paper, compostable plastic, canvas or glass? What is their carbon footprint in production stages? Research by several independent groups has revealed that these materials leave an even larger carbon footprint during their production. Data have shown that polyethylene plastic bags not only used lesser fuel and energy throughout production, they also emitted fewer global-warming gases and left lesser mass of solid wastes, when compared with paper bags and with compostable plastic bags. Being more durable than other materials, use of polyethylene bags are more energy friendly than use of paper bags. 

Research done on behalf of the American Chemistry Council has shown that replacing plastic would eventually do more harm to the environment than their use. Finally, consumer habits count. If people don’t reuse plastics, then its advantages over paper cease to exist. Of course, the problem of permanent waste and global health consequences are issues that cannot be overlooked. The solution might lie in using plastics more wisely and re-using them as much as possible. 

(Christopher Joyce, NPR

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Written by sciencepolicyforall

July 12, 2019 at 3:18 pm

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