Sublethal parasites in white-footed mice: impact on survival and reproduction

1991 ◽  
Vol 69 (2) ◽  
pp. 398-404 ◽  
Author(s):  
James C. Munger ◽  
William H. Karasov
Keyword(s):  
Population Density ◽  
Peromyscus Leucopus ◽  
Parasitic Infection ◽  
Reproductive Season ◽  
Natural Experiments ◽  
Bot Fly ◽  
Impact On Survival ◽  
Survival And Reproduction ◽  
Potential Impact ◽  
The Impact

The potential impact of two parasites on the population density of host white-footed mice (Peromyscus leucopus) was assessed by measuring effects on survival and reproduction in field populations. Thirty-eight mice infected with larvae of the bot fly Cuterebra angustifrons had their larvae removed, another 41 mice remained infected, and 46 other mice were naturally uninfected during the experiment. No effect of bot larvae removal was detected on either survival (measured as attrition) or reproduction (measured as end of reproductive season). However, contrary to expectation, naturally infected mice had lower attrition and a marginally longer reproductive season than naturally uninfected mice. This latter result is probably an artifact, due to underlying differences between naturally infected and uninfected mice. Sixty-seven mice were experimentally infected with the tapeworm Hymenolepis citelli (64 mice were controls), but no effect was detected on attrition from the trappable population nor on the cessation of the reproductive season. Our results indicate that (i) these parasites are unlikely to have any effect on population density of white-footed mice, and (ii) it is potentially misleading to use "natural experiments" (comparison of naturally infected hosts with uninfected hosts) to study the impact of parasitic infection.

scholarly journals Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e043010
Author(s):  
Jane Lyons ◽  
Ashley Akbari ◽  
Fatemeh Torabi ◽  
Gareth I Davies ◽  
Laura North ◽  
...  
Keyword(s):  
Policy Development ◽  
Healthcare Utilisation ◽  
Population Data ◽  
Population Level ◽  
Risk Groups ◽  
Service Utilisation ◽  
Natural Experiments ◽  
Spread Of Infection ◽  
The Impact

IntroductionThe emergence of the novel respiratory SARS-CoV-2 and subsequent COVID-19 pandemic have required rapid assimilation of population-level data to understand and control the spread of infection in the general and vulnerable populations. Rapid analyses are needed to inform policy development and target interventions to at-risk groups to prevent serious health outcomes. We aim to provide an accessible research platform to determine demographic, socioeconomic and clinical risk factors for infection, morbidity and mortality of COVID-19, to measure the impact of COVID-19 on healthcare utilisation and long-term health, and to enable the evaluation of natural experiments of policy interventions.Methods and analysisTwo privacy-protecting population-level cohorts have been created and derived from multisourced demographic and healthcare data. The C20 cohort consists of 3.2 million people in Wales on the 1 January 2020 with follow-up until 31 May 2020. The complete cohort dataset will be updated monthly with some individual datasets available daily. The C16 cohort consists of 3 million people in Wales on the 1 January 2016 with follow-up to 31 December 2019. C16 is designed as a counterfactual cohort to provide contextual comparative population data on disease, health service utilisation and mortality. Study outcomes will: (a) characterise the epidemiology of COVID-19, (b) assess socioeconomic and demographic influences on infection and outcomes, (c) measure the impact of COVID-19 on short -term and longer-term population outcomes and (d) undertake studies on the transmission and spatial spread of infection.Ethics and disseminationThe Secure Anonymised Information Linkage-independent Information Governance Review Panel has approved this study. The study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.

scholarly journals The Impact of Health Policies and Sociodemographic Factors on Doubling Time of the COVID-19 Pandemic in Mexico

2021 ◽  
Vol 18 (5) ◽  
pp. 2354
Author(s):  
Lina Díaz-Castro ◽  
Héctor Cabello-Rangel ◽  
Kurt Hoffman
Keyword(s):  
Population Density ◽  
Doubling Time ◽  
Sociodemographic Factors ◽  
Health Policies ◽  
Government Response ◽  
University Of Oxford ◽  
Negative Effect ◽  
Population Sizes ◽  
The University ◽  
The Impact

Background. The doubling time is the best indicator of the course of the current COVID-19 pandemic. The aim of the present investigation was to determine the impact of policies and several sociodemographic factors on the COVID-19 doubling time in Mexico. Methods. A retrospective longitudinal study was carried out across March–August, 2020. Policies issued by each of the 32 Mexican states during each week of this period were classified according to the University of Oxford Coronavirus Government Response Tracker (OxCGRT), and the doubling time of COVID-19 cases was calculated. Additionally, variables such as population size and density, poverty and mobility were included. A panel data model was applied to measure the effect of these variables on doubling time. Results. States with larger population sizes issued a larger number of policies. Delay in the issuance of policies was associated with accelerated propagation. The policy index (coefficient 0.60, p < 0.01) and the income per capita (coefficient 3.36, p < 0.01) had a positive effect on doubling time; by contrast, the population density (coefficient −0.012, p < 0.05), the mobility in parks (coefficient −1.10, p < 0.01) and the residential mobility (coefficient −4.14, p < 0.01) had a negative effect. Conclusions. Health policies had an effect on slowing the pandemic’s propagation, but population density and mobility played a fundamental role. Therefore, it is necessary to implement policies that consider these variables.

scholarly journals Impact of temperature and relative humidity on the transmission of COVID-19: a modelling study in China and the United States

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e043863
Author(s):  
Jingyuan Wang ◽  
Ke Tang ◽  
Kai Feng ◽  
Xin Lin ◽  
Weifeng Lv ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Relative Humidity ◽  
Human Mobility ◽  
The United States ◽  
Reproductive Number ◽  
Cross Sectional ◽  
The Usa ◽  
Higher Temperature ◽  
Potential Impact ◽  
The Impact

ObjectivesWe aim to assess the impact of temperature and relative humidity on the transmission of COVID-19 across communities after accounting for community-level factors such as demographics, socioeconomic status and human mobility status.DesignA retrospective cross-sectional regression analysis via the Fama-MacBeth procedure is adopted.SettingWe use the data for COVID-19 daily symptom-onset cases for 100 Chinese cities and COVID-19 daily confirmed cases for 1005 US counties.ParticipantsA total of 69 498 cases in China and 740 843 cases in the USA are used for calculating the effective reproductive numbers.Primary outcome measuresRegression analysis of the impact of temperature and relative humidity on the effective reproductive number (R value).ResultsStatistically significant negative correlations are found between temperature/relative humidity and the effective reproductive number (R value) in both China and the USA.ConclusionsHigher temperature and higher relative humidity potentially suppress the transmission of COVID-19. Specifically, an increase in temperature by 1°C is associated with a reduction in the R value of COVID-19 by 0.026 (95% CI (−0.0395 to −0.0125)) in China and by 0.020 (95% CI (−0.0311 to −0.0096)) in the USA; an increase in relative humidity by 1% is associated with a reduction in the R value by 0.0076 (95% CI (−0.0108 to −0.0045)) in China and by 0.0080 (95% CI (−0.0150 to −0.0010)) in the USA. Therefore, the potential impact of temperature/relative humidity on the effective reproductive number alone is not strong enough to stop the pandemic.

scholarly journals Using syndromic measures of mortality to capture the dynamics of COVID-19 in Java, Indonesia, in the context of vaccination rollout

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Bimandra A. Djaafara ◽  
Charles Whittaker ◽  
Oliver J. Watson ◽  
Robert Verity ◽  
Nicholas F. Brazeau ◽  
...  
Keyword(s):  
Rural Areas ◽  
Vaccination Campaign ◽  
Control Measures ◽  
Additional Insight ◽  
Short Term ◽  
If Current ◽  
Vaccine Impact ◽  
Potential Impact ◽  
The Impact ◽  
Insight Into

Abstract Background As in many countries, quantifying COVID-19 spread in Indonesia remains challenging due to testing limitations. In Java, non-pharmaceutical interventions (NPIs) were implemented throughout 2020. However, as a vaccination campaign launches, cases and deaths are rising across the island. Methods We used modelling to explore the extent to which data on burials in Jakarta using strict COVID-19 protocols (C19P) provide additional insight into the transmissibility of the disease, epidemic trajectory, and the impact of NPIs. We assess how implementation of NPIs in early 2021 will shape the epidemic during the period of likely vaccine rollout. Results C19P burial data in Jakarta suggest a death toll approximately 3.3 times higher than reported. Transmission estimates using these data suggest earlier, larger, and more sustained impact of NPIs. Measures to reduce sub-national spread, particularly during Ramadan, substantially mitigated spread to more vulnerable rural areas. Given current trajectory, daily cases and deaths are likely to increase in most regions as the vaccine is rolled out. Transmission may peak in early 2021 in Jakarta if current levels of control are maintained. However, relaxation of control measures is likely to lead to a subsequent resurgence in the absence of an effective vaccination campaign. Conclusions Syndromic measures of mortality provide a more complete picture of COVID-19 severity upon which to base decision-making. The high potential impact of the vaccine in Java is attributable to reductions in transmission to date and dependent on these being maintained. Increases in control in the relatively short-term will likely yield large, synergistic increases in vaccine impact.

scholarly journals Conceptualising natural and quasi experiments in public health

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Frank de Vocht ◽  
Srinivasa Vittal Katikireddi ◽  
Cheryl McQuire ◽  
Kate Tilling ◽  
Matthew Hickman ◽  
...  
Keyword(s):  
Public Health ◽  
Study Design ◽  
Grey Literature ◽  
Public Health Research ◽  
Natural Experiments ◽  
Target Trial ◽  
Design Elements ◽  
Randomized Controlled ◽  
Study Designs ◽  
The Impact

Abstract Background Natural or quasi experiments are appealing for public health research because they enable the evaluation of events or interventions that are difficult or impossible to manipulate experimentally, such as many policy and health system reforms. However, there remains ambiguity in the literature about their definition and how they differ from randomized controlled experiments and from other observational designs. We conceptualise natural experiments in the context of public health evaluations and align the study design to the Target Trial Framework. Methods A literature search was conducted, and key methodological papers were used to develop this work. Peer-reviewed papers were supplemented by grey literature. Results Natural experiment studies (NES) combine features of experiments and non-experiments. They differ from planned experiments, such as randomized controlled trials, in that exposure allocation is not controlled by researchers. They differ from other observational designs in that they evaluate the impact of events or process that leads to differences in exposure. As a result they are, in theory, less susceptible to bias than other observational study designs. Importantly, causal inference relies heavily on the assumption that exposure allocation can be considered ‘as-if randomized’. The target trial framework provides a systematic basis for evaluating this assumption and the other design elements that underpin the causal claims that can be made from NES. Conclusions NES should be considered a type of study design rather than a set of tools for analyses of non-randomized interventions. Alignment of NES to the Target Trial framework will clarify the strength of evidence underpinning claims about the effectiveness of public health interventions.

scholarly journals Research on the Economic Development Threshold Effect of the Employment Density of the Shanghai Consumer Goods Industry in the Context of New Manufacturing, Based on the Experience Comparison with International Metropolis

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 969
Author(s):  
Lei Shen ◽  
Xi Zhang ◽  
Hongda Liu ◽  
Pinbo Yao
Keyword(s):  
Economic Development ◽  
Population Density ◽  
Consumer Goods ◽  
Inflection Point ◽  
Growth Potential ◽  
Positive Trend ◽  
Employment Density ◽  
Consumer Goods Industry ◽  
The Impact ◽  
Development Threshold

With the rise of a new generation of technology and industrial changes, the service-oriented manufacturing industry has become the direction of future development. With the background of new manufacturing, this paper constructs an economic development threshold model of employment density of consumer goods industry based on data from Shanghai and Tokyo from 2007 to 2016, and empirically analyzes the impact of the employment density of the consumer goods industry on urban economic development under different population densities. At the same time, by comparing the experience of Tokyo, the development status and prospects of Shanghai’s consumer goods industry are explored. The study found that the threshold of Tokyo’s consumer goods industry is 0.608. When population density is lower than this threshold, the consumer goods industry continues to promote the economic development of Tokyo; however, when the population density is higher than this threshold, the consumer goods industry begins to inhibit the economic development of Tokyo. The Shanghai consumer goods industry threshold is 0.329. Under the threshold, most of the consumer goods industry contributions to the economy are negative, but above the threshold, they begin to show a positive trend. The inflection point of the effect curve of Tokyo’s consumer goods industry on economic development has appeared, but the inflection point of Shanghai’s consumer goods industry has not yet appeared. Compared with Tokyo, the economic vitality of Shanghai’s consumer goods industry has not yet been fully released. With the continued increase of population density in Shanghai, the growth potential of the consumer goods industry is huge, and it is expected to reshape the flourishing age of Shanghai’s light industry brand.

scholarly journals China’s Investments in Germany and the Impact of the COVID-19 Pandemic

2021 ◽  
Vol 56 (2) ◽  
pp. 113-119
Author(s):  
Xinming Xia ◽  
Wan-Hsin Liu
Keyword(s):  
Large Scale ◽  
Know How ◽  
Advanced Technologies ◽  
The Future ◽  
Potential Impact ◽  
Chinese State ◽  
The Impact ◽  
Gain Access ◽  
Over Time

AbstractThis paper analyses how China’s investments in Germany have developed over time and the potential impact of the COVID-19 pandemic in this regard, based on four different datasets, including our own survey in mid-2020. Our analysis shows that Germany is currently one of the most attractive investment destinations for Chinese investors. Chinese state-owned enterprises have played an important role as investors in Germany — particularly in large-scale projects. The COVID-19 pandemic has had some negative but rather temporary effects on Chinese investments in Germany. Germany is expected to stay attractive to Chinese investors who seek to gain access to advanced technologies and know-how in the future.

scholarly journals Indirect cholinergic activation slows down pancreatic cancer growth and tumor-associated inflammation

2020 ◽  
Vol 39 (1) ◽  
Author(s):  
Paulo L. Pfitzinger ◽  
Laura Fangmann ◽  
Kun Wang ◽  
Elke Demir ◽  
Engin Gürlevik ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Mouse Model ◽  
Tumor Stage ◽  
Ache Inhibitors ◽  
Impact On Survival ◽  
The Impact ◽  
Ache Expression ◽  
Cholinergic Activation

Abstract Background Nerve-cancer interactions are increasingly recognized to be of paramount importance for the emergence and progression of pancreatic cancer (PCa). Here, we investigated the role of indirect cholinergic activation on PCa progression through inhibition of acetylcholinesterase (AChE) via clinically available AChE-inhibitors, i.e. physostigmine and pyridostigmine. Methods We applied immunohistochemistry, immunoblotting, MTT-viability, invasion, flow-cytometric-cell-cycle-assays, phospho-kinase arrays, multiplex ELISA and xenografted mice to assess the impact of AChE inhibition on PCa cell growth and invasiveness, and tumor-associated inflammation. Survival analyses were performed in a novel genetically-induced, surgically-resectable mouse model of PCa under adjuvant treatment with gemcitabine+/−physostigmine/pyridostigmine (n = 30 mice). Human PCa specimens (n = 39) were analyzed for the impact of cancer AChE expression on tumor stage and survival. Results We discovered a strong expression of AChE in cancer cells of human PCa specimens. Inhibition of this cancer-cell-intrinsic AChE via pyridostigmine and physostigmine, or administration of acetylcholine (ACh), diminished PCa cell viability and invasion in vitro and in vivo via suppression of pERK signaling, and reduced tumor-associated macrophage (TAM) infiltration and serum pro-inflammatory cytokine levels. In the novel genetically-induced, surgically-resectable PCa mouse model, adjuvant co-therapy with AChE blockers had no impact on survival. Accordingly, survival of resected PCa patients did not differ based on tumor AChE expression levels. Patients with higher-stage PCa also exhibited loss of the ACh-synthesizing enzyme, choline-acetyltransferase (ChAT), in their nerves. Conclusion For future clinical trials of PCa, direct cholinergic stimulation of the muscarinic signaling, rather than indirect activation via AChE blockade, may be a more effective strategy.

scholarly journals The potentially hazardous NEA 2001 BB16

2019 ◽  
Vol 28 (1) ◽  
pp. 180-190
Author(s):  
Ireneusz Wlodarczyk
Keyword(s):  
Mean Value ◽  
Optical Observations ◽  
Uniform Sampling ◽  
The Earth ◽  
22Nd Century ◽  
Lyapunov Time ◽  
Gravitational Model ◽  
Calculated Probability ◽  
Potential Impact ◽  
The Impact

AbstractWe computed the impact solutions of the potentially dangerous Near Earth Asteroid (NEA) 2001 BB16 based on 47 optical observations from January 20.08316 UTC, 2001, through February 09.15740 UTC, 2016, and one radar observation from January 19.90347 UTC, 2016. We used two methods to sample the starting Line of Variation (LOV). First method, called thereafter LOV1, with the uniform sampling of the LOV parameter, out to LOV = 5 computing 3000 virtual asteroids (VAs) on both sides of the LOV, which gives 6001 VAs and propagated their orbits to JD2525000.5 TDT=February 12, 2201. We computed the non-gravitational parameterA2=(34.55±7.38)·10–14 au/d2 for nominal orbit of 2001 BB16 and possible impacts with the Earth until 2201. For potential impact in 2195 we find A2=20.0·10−14 au/d2. With a positive value of A2, 2001 BB16 can be prograde rotator. Moreover, we computed Lyapunov Time (LT) for 2001 BB16, which for all VAs, has a mean value of about 25 y. We showed that impact solutions, including the calculated probability of a possible collision of a 2001 BB16 asteroid with the Earth depends on how to calculate and take into account the appropriate gravitational model, including the number of perturbing massive asteroids. In some complicated cases, it may depend also on the number of clones calculated for a given sigma LOV1. The second method of computing the impact solutions, called thereafter LOV2, is based on a non-uniformly sampling of the LOV. We showed that different methods of sampling the LOV can give different impact solutions, but all computed dates of possible impacts of the asteroid 2001 BB16 with the Earth occur in accordance at the end of the 22nd century.

Patients With Invasive Breast Cancer Who Refuse Treatment: An Analysis of Associated Factors and Impact on Survival

2021 ◽  
pp. 000313482110241
Author(s):  
Jackelyn J. Moya ◽  
Ashkan Moazzez ◽  
Junko J. Ozao-Choy ◽  
Christine Dauphine
Keyword(s):  
Breast Cancer ◽  
Endocrine Therapy ◽  
Invasive Breast Cancer ◽  
Risk Groups ◽  
Breast Cancer Treatment ◽  
Study Cohort ◽  
National Cancer Database ◽  
Optimal Outcomes ◽  
Impact On Survival ◽  
The Impact

Background Completion of surgical resection and adjuvant/neoadjuvant treatments (chemotherapy, radiation, and endocrine therapy) is necessary to achieve optimal outcomes in invasive breast cancer. The objective of this study was to determine the characteristics of patients refusing treatment and to analyze the impact of refusal on survival. Study Design A retrospective cohort study of invasive breast cancer cases diagnosed 2004-2016 was performed utilizing the National Cancer Database. Results Of 2 058 568 cases comprising the study cohort, .6% refused recommended surgery, 14.1% refused chemotherapy, 5.5% refused radiation, and 6.3% refused endocrine therapy. Patients refusing therapy were older and more likely uninsured; they did not live farther from the treating hospital. Racial disparities were also associated with refusal. Surgery refusal had the highest hazard ratio for mortality (2.7; 95% CI: 2.5-3.0, P < .001) compared to chemotherapy (1.3; 95% CI: 1.3-1.4, P < .001), radiation (1.8; 95% CI: 1.7-1.9, P < .001), and endocrine therapy (1.5; 95% CI: 1.4-1.6, P < .001) independent of race, insurance, receptor status, and stage. Conclusion This study demonstrates significant associations with refusal of breast cancer treatment and quantifies the impact on mortality, which may help to identify at-risk groups for whom interventions could prevent increases in mortality associated with declining treatment.

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