Read the complete Statistical Guidelines here The cornerstone of research credibility and reproducibility lies in ensuring that research is conducted and reported in an accurate manner. These values are reflected in PLOS ONE Criteria for
The post Worms in the Big Apple: Identifying Patterns of Toxocariasis Infection in New York City appeared first on EveryONE.
The Black Death, a pandemic at its height in Europe during the mid-14th century, was a virulent killer. It was so effective that it wiped out approximately one third of Europe’s population. Recent studies have shown that the elderly and the sick were most susceptible. But was the Black Death a “smart” killer?
A recent PLOS ONE study indicates that the Black Death’s virulence might have affected genetic variation in the surviving human population by reducing frailty, resulting in less virulent subsequent outbreaks of the plague. By examining the differences in survival rates and mortality risks in both pre-Black Death and post-Black Death samples of a London population—in combination with other, extrinsic factors, like differences in diet between the two groups—the researcher found that in London, on average, people lived longer following the plague than they did before it, despite repeated plague outbreaks. In other words, in terms of genetic variation, the Black Death positively affected the health of the surviving population.
To uncover differences in the health of medieval Londoners, Dr. Sharon DeWitte of the University of South Carolina examined 464 pre-Black Death individuals from three cemeteries and 133 post-Black Death individuals from one. She chose a diverse range of samples for a comprehensive view of the population, including both the rich and the poor, and women and children, but targeted one geographic location: London.
The ages-at-death of the samples were determined by calculating best estimates—in statistics these are called point estimates—based on particular indicators of age found on the skeletons’ hip and skull bones. Individuals’ ages were then evaluated against those in the Anthropological Database of Odense University, a pre-existing database comprising the Smithsonian’s Terry Collection and prior age-at-death data from 17th-century Danish parish records.
After estimating how old these individuals were when they died and comparing the age indicators against the Odense reference tool, the author conducted statistical analyses on the data to examine what the ages-at-death could tell us about the proportion of pre- and post- Black Death medieval Londoners who lived to a ripe old age, as well as the likelihood of death.
Survivorship was estimated using the Kaplan-Meier Estimator, a function used to indicate a quantity based on known data; in this case the function evaluated how long people lived in a given time period (pre-Black Death or post-Black Death). The calculated differences were significant: In particular, the proportion of adults who lived beyond the age of 50 from the post-Black Death group was much greater than those from the pre-Black Death group.
In the pre-Black Death group, death was most likely to occur between the ages of 10 and 19, as seen above.
The Kaplan-Meier survival plot shows how the chances of survival, which decrease with age, differ for Pre-Black Death and Post-Black Death groups, as seen below.
As the survival plot indicates, post-Black Death Londoners lived longer than there Pre-Black Death predecessors.
Finally, Dr. DeWitte estimated the risk of mortality by applying the age data to the statistical model known as the Gompertz hazard, which shows the typical pattern of increased risk in mortality with age. She found that overall post-Black Death Londoners faced lower risks of mortality than their pre-Black Death counterparts.
To make long and complicated methodology short, these analyses indicate that post-Black Death Londoners appear to have lived longer than pre-Black Death Londoners. The author estimates that the general population of London enjoyed a period of about 200 years of improved survivorship, based on these results.
The virulent killer, the Black Death, may have helped select for a healthier London by influencing genetic variation, at least in the short term. However, to better understand the improved quality of life of post-Black Death London, the author suggests further study to disentangle two major factors: the selectivity of the Black Death, coupled with improvements in lifestyle for post-Black Death individuals. For example, the massive depopulation in Europe resulted in increased wages for workers and improvements to diet following the plague, which also likely improved health for medieval Londoners. By unraveling intrinsic, biological changes in genetic variation from outside extrinsic factors like improvements in diet, it may be possible to better understand the aftermath of one of the most devastating killers in infectious disease history.
The EveryONE blog has more on the medieval killer here.
Citation: DeWitte SN (2014) Mortality Risk and Survival in the Aftermath of the Medieval Black Death. PLoS ONE 9(5): e96513. doi:10.1371/journal.pone.0096513
Image 2: pone.0096513
Image 3: pone.0096513
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Those of us who commute to the PLOS San Francisco office have noticed the emergence of bike share stations cropping up along the San Francisco Bay and on the city’s main drag. And we’re not alone here in San Francisco: the picture above is from the New York City Department of Transportation’s bike share. Around the world, bike share systems, which aim to make bicycles available on a short-term basis to anyone, have experienced massive growth as cities work to decrease gas emissions and encourage people to stay active. However, not everyone is ready to forgo the convenience of four wheels for two just yet. To understand why more people haven’t made the switch from cars to bike share systems, the author of a recently published PLOS ONE paper delved into possible factors affecting our willingness to don a helmet and cycle the distance.
Using publically available data from Washington DC and Boston, Dr. Jurdak, an Australian researcher, conducted a series of statistical analyses designed to examine the impact of bike share system pricing and neighborhood layout on potential bikers. It turns out cost is a major factor for commuters and tourists alike, but distance is not. Although analyses showed a bias towards shorter trips with a tendency towards a peak of 6 minutes—averaging 13 minutes per trip—a sharp drop off occurred in the likelihood of trips right around 30 minutes.
Why the decline at around 30 minutes? In both Boston and Washington DC, trips under 30 minutes incurred no additional cost in the bike share pricing system. Registered users of the bike share, typically commuters, must pay an initial registration fee but have a grace period for all trips completed in less than 30 minutes. Trips extending beyond 30 minutes, however, incur additional fees. In other words, public bicyclers are looking to maximize the distance biked and time spent without incurring any additional cost. Researchers have labeled this as ‘cost sensitivity.’
Statistical analyses also demonstrated the same cost sensitivity in casual users, or those who do not have a monthly or annual membership, and who likely use the bike share system for tourism. However, instead of noting a decline in the likelihood of trips around 30 minutes, Dr. Jurdak found a decline for casual users at around 60 minutes (another price point).
On the other hand, despite sensitivity to cost, bikers appeared less dissuaded from bike trips based on neighborhood layout. Although stations in Boston were on average much closer to other nearby stations than in Washington DC, in general, the trip distribution for both cities was remarkably similar. Perhaps not surprisingly, the most popular routes taken in both Boston and Washington DC were relatively flat.
To encourage more people to cut the car usage and grab a rental bike, Dr. Jurdak recommends that cities consider incentivizing their constituents with what they care about: cost. Modified prices for bike rental during peak hours may decrease car traffic on congested roads; an extension of grace periods for biking difficult topology, like up a steep San Francisco hill, might encourage us to bike even though the clock is ticking to 30 minutes and an incurred rise in price. As cities look to evolve public transportation systems and increase responsible urban mobility, and as city dwellers look for cost-effective ways to get around, bike share programs continue to offer healthy solutions for all, even at 30 minutes or less.
Jurdak R (2013) The Impact of Cost and Network Topology on Urban Mobility: A Study of Public Bicycle Usage in 2 U.S. Cities. PLoS ONE 8(11): e79396. doi:10.1371/journal.pone.0079396
Readers of this blog will have noticed the occasional notification of new exceptions that have been added to RoMEO.
But what are these exceptions and why are they important?
RoMEO has traditionally focussed on the general policies of publishers, those that cover the majority of their journals titles. However, some titles may have a different embargo period or use a Creative Commons License. Although, we have tried to impart this information under the General Conditions field, it has become cumbersome and still requires users to investigate themselves as to which embargo period applies to their journal of interest.
We started adding exceptions in November 2011, and are continuing the process as they are identified and we clarify the policy exceptions with publishers.
Some exceptions will cover only one journal title, others much more.
To date RoMEO lists a total of 59 exceptions, from 25 Publishers. We are still working through publishers we have identified as having possible exceptions and hope to add more in the future.
A list of the Exceptions added so far:
- Akademie Ved Ceske Republiky, Knihovna
- Knihy a dejiny [6/3/12]
- American Medical Association
- JAMA [17/11/11]
- American Society for Microbiology
- mBio [26/4/12]
- Bulletin – [17/11/11]
- JASIS&T – [17/11/11]
- American Society of Clinical Oncology
- JCO [29/11/11]
- JOP [29/11/11]
- BMJ Publishing Group
- BMJ [30/1/12]
- BMj Open [18/4/12]
- Analise [18/4/12]
- BELT [18/4/12]
- EDP Sciences
- EDJ [26/4/12]
- Creative Commons Attribution Non-Commercial [26/4/12]
- Institut Français d’Etudes Andines (IFEA)
- Bulletin de l’IFEA [23/3/12]
- Laboratório Nacional de Energia e Geologia
- Corrosão e Protecção de Materiais [13/12/11]
- MIT Press
- STM [17/11/11]
- Arts and Humanities [17/11/11]
- Economics [17/11/11]
- Oxford University Press
- Policy A – [16/11/11]
- Policy A1 – [15/11/11]
- Policy B – [16/11/11]
- Policy B1 – [15/11/11]
- Policy C – [16/11/11]
- Policy D – [15/11/11]
- Policy E – [16/11/11]
- Policy F – [15/11/11]
- Policy G – [15/11/11]
- Policy H – [15/11/11]
- Policy I – [15/11/11]
- Policy J – [15/11/11]
- Policy K – [15/11/11]
- Policy L – [15/11/11]
- Policy M – [15/11/11]
- Policy N – [16/11/11]
- Policy O – [15/11/11]
- Policy P [12/9/12]
- Policy Q [12/9/12]
- i-Perception [10/5/12]
- Perception [10/5/12]
- Royal Society
- Open Biology [19/7/12]
- Taylor & Francis
- SSH Titles [5/12/11]
- STM Titles [5/12/11]
- Taylor & Francis (Psychology Press)
- STM Titles [5/12/11]
- Taylor & Francis (Routledge)
- LIS Titles [1/12/11]
- SSH Titles [1/12/11]
- STM Titles [1/12/11]
- Universidad de Murcia [14/9/12]
- Glosas Didacticas
- Universidade de Brasilia
- Attribution Non-Commercial [17/9/12]
- Attribution Non-Commercial No-Derivatives [17/9/12]
- Attribution Non-Commercial Share-Alike [17/9/12]
- Universite Paris 3, Institut des Hautes Etudes de l’Amérique Latine (IHEAL) [3/1/12]
- Cahiers des Ameriques Latines
- Univ Chig Press
- Publications of the Astronomical Society of the Pacific [17/11/11]
- Università degli Studi di Milano (University of Milan)
- Attribution [17/4/12]
- Share Alike [17/4/12]
- Enthymema [17/4/12]
- Uni of Texas Press
- Cinema Journal [17/11/11]
- Vittorio Klostermann
- ZfBB [29/11/11]
- Wildlife Society
- Journal of Wildlife Management [18/4/12]