ON THE USE OF MECHANISTIC AND DATA-DRIVEN MODELS IN POPULATION DYNAMICS: THE CASE OF TUBERCULOSIS IN THE US OVER THAT PAST TWO CENTURIES

BIOMAT 2010 ◽  
2011 ◽  
Author(s):  
JUAN PABLO APARICIO ◽  
CARLOS CASTILLO-CHAVEZ
Keyword(s):  
Population Dynamics ◽  
Data Driven ◽  
The Us

scholarly journals Analysis of 220 Years of Floodplain Population Dynamics in the US at Different Spatial Scales

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 141
Author(s):  
Firoza Akhter ◽  
Maurizio Mazzoleni ◽  
Luigia Brandimarte
Keyword(s):  
Population Dynamics ◽  
Large Scale ◽  
Spatial Scales ◽  
National Level ◽  
State Level ◽  
Economic Activities ◽  
Protection Measures ◽  
Management Planning ◽  
The Us ◽  
Over Time

In this study, we explore the long-term trends of floodplain population dynamics at different spatial scales in the contiguous United States (U.S.). We exploit different types of datasets from 1790–2010—i.e., decadal spatial distribution for the population density in the US, global floodplains dataset, large-scale data of flood occurrence and damage, and structural and nonstructural flood protection measures for the US. At the national level, we found that the population initially settled down within the floodplains and then spread across its territory over time. At the state level, we observed that flood damages and national protection measures might have contributed to a learning effect, which in turn, shaped the floodplain population dynamics over time. Finally, at the county level, other socio-economic factors such as local flood insurances, economic activities, and socio-political context may predominantly influence the dynamics. Our study shows that different influencing factors affect floodplain population dynamics at different spatial scales. These facts are crucial for a reliable development and implementation of flood risk management planning.

scholarly journals Data-Driven Study on the Sustainable Log Movements: Impact of Rail Car Fleet Size on Freight Storage and Car Idling

2020 ◽  
Vol 12 (11) ◽  
pp. 4563
Author(s):  
Sangpil Ko ◽  
Pasi Lautala ◽  
Kuilin Zhang
Keyword(s):  
Service Life ◽  
Seasonal Dynamics ◽  
Lake Superior ◽  
Data Driven ◽  
Short Term ◽  
Fleet Size ◽  
Interesting Observation ◽  
The Us ◽  
Term Storage ◽  
Scale Data

Rail car availability and the challenges associated with the seasonal dynamics of log movements have received growing attentions in the Lake Superior region of the US, as a portion of rail car fleet is close to reaching the end of its service life. This paper proposes a data-driven study on the rail car peaking issue to explore the fleet of rail cars dedicated to being used for log movements in the region, and to evaluate how the number of cars affects both the storage need at the sidings and the time the cars are idled. This study is based on the actual log scale data collected from a group of forest companies in cooperation with the Lake State Shippers Association (LSSA). The results of our analysis revealed that moving the current log volumes in the region would require approximately 400–600 dedicated and shared log cars in ideal conditions, depending on the specific month. While the higher fleet size could move the logs as they arrive to the siding, the lower end would nearly eliminate the idling of rail cars and enable stable volumes throughout the year. However, this would require short-term storage and additional handling of logs at the siding, both elements that increase the costs for shippers. Another interesting observation was the fact that the reduction of a single day in the loading/unloading process (2.5 to 1.5 days) would eliminate almost 100 cars (20%) of the fleet without reduction in throughput.

scholarly journals Interchangeability of biosimilars: A study of expert views and visions regarding the science and substitution

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0262537
Author(s):  
Louise C. Druedahl ◽  
Sofia Kälvemark Sporrong ◽  
Timo Minssen ◽  
Hans Hoogland ◽  
Marie Louise De Bruin ◽  
...  
Keyword(s):  
Pharmaceutical Industry ◽  
Scientific Data ◽  
Data Driven ◽  
Policy Debate ◽  
Structured Interviews ◽  
Study Objective ◽  
Scientific Certainty ◽  
The Us ◽  
Almost All ◽  
Near Future

Healthcare systems have reached a critical point regarding the question of whether biosimilar substitution should become common practice. To move the discussion forward, the study objective was to investigate the views of experts from medicines agencies and the pharmaceutical industry on the science underpinning interchangeability of biosimilars. We conducted an empirical qualitative study using semi-structured interviews informed by a cross-disciplinary approach encompassing regulatory science, law, and pharmaceutical policy. In total 25 individuals with experience within biologics participated during September 2018–August 2019. Eight participants were EU national medicines authority regulators, and 17 had pharmaceutical industry background: five from two originator-only companies, four from two companies with both biosimilar and originator products, and eight from seven biosimilar-only companies. Two analysts independently conducted inductive content analysis, resulting in data-driven themes capturing the meaning of the data. The participants reported that interchangeability was more than a scientific question of likeness between biosimilar and reference products: it also pertained to regulatory practices and trust. Participants were overall confident in the science behind exchanging biosimilar products for the reference products via switching, i.e., with physician involvement. However, their opinions differed regarding the scientific risk associated with biosimilar substitution, i.e., without physician involvement. Almost all participants saw no need for additional scientific data to support substitution. Moreover, the participants did not believe that switching studies, as required in the US, were appropriate for obtaining scientific certainty due to their small size. It is unclear why biosimilar switching is viewed as scientifically safer than substitution; therefore, we expect greater policy debate on biosimilar substitution in the near future. We urge European and UK policymakers and regulators to clarify their visions for biosimilar substitution; the positions of these two frontrunners are likely to influence other jurisdictions on the future of biosimilar use.

Kyrgyzstan

2017 ◽  
pp. 404-426
Author(s):  
Mehmet Yüce
Keyword(s):  
Foreign Policy ◽  
Population Dynamics ◽  
Economic Cooperation ◽  
The State ◽  
Ethnic Composition ◽  
Kyrgyz Republic ◽  
Social Infrastructure ◽  
The West ◽  
The Us ◽  
Education Culture

Kyrgyzstan is very rich and striking with its ethnic composition. After the collapse of USSR, the changes in social infrastructure and the differentiation in the ideological premises of the state have led to a dramatic change in the population dynamics of the country. Now, the Kyrgyzstan Republic is a democratic and secular state. Ethnic structure, border security, long border with China are important issues of Kyrgyzstan, which, in its foreign policy, has drawn a profile that is open to the west, avoids conflicts with its neighbors, pursues a balanced policy in its relations with the US, Russia and China. Turkey is also an important partner of Kyrgyzstan; between Turkey and the Kyrgyz Republic, over 100 agreements and cooperation documents were signed in the fields of education, culture, trade and economic cooperation, transport, communication, military and other areas.

Foliar nematode, Litylenchus crenatae ssp. mccannii , population dynamics in leaves and buds of beech leaf disease-affected trees in Canada and the US

2020 ◽  
Vol 50 (3) ◽  
pp. e12599
Author(s):  
Sharon E. Reed ◽  
Sylvia Greifenhagen ◽  
Qing Yu ◽  
Adam Hoke ◽  
David J. Burke ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Leaf Disease ◽  
The Us ◽  
Foliar Nematode

scholarly journals Suicide disparities across metropolitan areas in the US: A comparative assessment of socio-environmental factors using a data-driven predictive approach

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0258824
Author(s):  
Sayanti Mukherjee ◽  
Zhiyuan Wei
Keyword(s):  
Environmental Factors ◽  
Goodness Of Fit ◽  
Metropolitan Areas ◽  
Predictive Accuracy ◽  
Climatic Factors ◽  
Data Driven ◽  
Us States ◽  
Suicide Rates ◽  
Significant Difference ◽  
The Us

Disparity in suicide rates across various metropolitan areas in the US is growing. Besides personal genomics and pre-existing mental health conditions affecting individual-level suicidal behaviors, contextual factors are also instrumental in determining region-/community-level suicide risk. However, there is a lack of quantitative approach to model the complex associations and interplays of the socio-environmental factors with the regional suicide rates. In this paper, we propose a holistic data-driven framework to model the associations of socio-environmental factors (demographic, socio-economic, and climate) with the suicide rates, and compare the key socio-environmental determinants of suicides across the large and medium/small metros of the vulnerable US states, leveraging a suite of advanced statistical learning algorithms. We found that random forest outperforms all the other models in terms of both in-sample goodness-of-fit and out-of-sample predictive accuracy, which is then used for statistical inferencing. Overall, our findings show that there is a significant difference in the relationships of socio-environmental factors with the suicide rates across the large and medium/small metropolitan areas of the vulnerable US states. Particularly, suicides in medium/small metros are more sensitive to socio-economic and demographic factors, while that in large metros are more sensitive to climatic factors. Our results also indicate that non-Hispanics, native Hawaiian or Pacific islanders, and adolescents aged 15-29 years, residing in the large metropolitan areas, are more vulnerable to suicides compared to those living in the medium/small metropolitan areas. We also observe that higher temperatures are positively associated with higher suicide rates, with large metros being more sensitive to such association compared to that of the medium/small metros. Our proposed data-driven framework underscores the future opportunities of using big data analytics in analyzing the complex associations of socio-environmental factors and inform policy actions accordingly.

scholarly journals The Lyme and Tickborne Disease Dashboard: A map-based resource to promote public health awareness and research collaboration

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260122
Author(s):  
Frank C. Curriero ◽  
Cara Wychgram ◽  
Alison W. Rebman ◽  
Anne E. Corrigan ◽  
Anton Kvit ◽  
...  
Keyword(s):  
Public Health ◽  
Spatial Data ◽  
Scientific Collaboration ◽  
One Health ◽  
Research Collaboration ◽  
Data Driven ◽  
Data Sets ◽  
Future Directions ◽  
The Us ◽  
Spatial Data Sets

With the incidence of Lyme and other tickborne diseases on the rise in the US and globally, there is a critical need for data-driven tools that communicate the magnitude of this problem and help guide public health responses. We present the Johns Hopkins Lyme and Tickborne Disease Dashboard (https://www.hopkinslymetracker.org/), a new tool that harnesses the power of geography to raise awareness and fuel research and scientific collaboration. The dashboard is unique in applying a geographic lens to tickborne diseases, aiming not only to become a global tracker of tickborne diseases but also to contextualize their complicated geography with a comprehensive set of maps and spatial data sets representing a One Health approach. We share our experience designing and implementing the dashboard, describe the main features, and discuss current limitations and future directions.

scholarly journals Implications of delayed reopening in controlling the COVID-19 surge in Southern and West-Central USA

2020 ◽  
Author(s):  
Raj Dandekar ◽  
Emma Wang ◽  
George Barbastathis ◽  
Chris Rackauckas
Keyword(s):  
Data Driven ◽  
Us States ◽  
Infected Case ◽  
West Central ◽  
Case Count ◽  
Proposed Model ◽  
The Us ◽  
June July ◽  
Central Usa

1SUMMARYIn the wake of the rapid surge in the Covid-19 infected cases seen in Southern and West-Central USA in the period of June-July 2020, there is an urgent need to develop robust, data-driven models to quantify the effect which early reopening had on the infected case count increase. In particular, it is imperative to address the question: How many infected cases could have been prevented, had the worst affected states not reopened early? To address this question, we have developed a novel Covid-19 model by augmenting the classical SIR epidemiological model with a neural network module. The model decomposes the contribution of quarantine strength to the infection timeseries, allowing us to quantify the role of quarantine control and the associated reopening policies in the US states which showed a major surge in infections. We show that the upsurge in the infected cases seen in these states is strongly co-related with a drop in the quarantine/lockdown strength diagnosed by our model. Further, our results demonstrate that in the event of a stricter lockdown without early reopening, the number of active infected cases recorded on 14 July could have been reduced by more than 40% in all states considered, with the actual number of infections reduced being more than 100, 000 for the states of Florida and Texas. As we continue our fight against Covid-19, our proposed model can be used as a valuable asset to simulate the effect of several reopening strategies on the infected count evolution; for any region under consideration.

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