Extra Mortality Research Articles

Protective Effect of Extra Virgin Olive Oil on Cancers, Gastrointestinal Cancers, and All-Cause Mortality: A Competing Risk Analysis in a Southern Italian Cohort.

This study investigates the association between extra virgin olive oil (EVOO) consumption and mortality risk in a cohort of Italian adults adhering to the Mediterranean diet. In a 17-year follow-up study involving participants from Castellana Grotte, Italy (2005-2023), we analyzed dietary intake and mortality data. Participants were categorized into three EVOO consumption groups: <30 g/day, 30-50 g/day, and >50 g/day. Mortality Hazard Ratios (HR) and Subdistribution Hazard Ratios (SHR) were calculated to assess the relationship between EVOO intake and all-cause and cancer mortality. Higher EVOO consumption was associated with significantly reduced cancer and all-cause mortality. Specifically, the daily intake of 30-50 g of EVOO was linked to a 24% lower risk of all-cause mortality (HR 0.77; 95% CI 0.63-0.93), while the consumption of more than 50 g/day was associated with a 20% reduction (HR 0.80; 95% CI 0.65-0.98). The most pronounced benefit was observed for gastrointestinal cancers, with a 60% lower mortality risk for those consuming over 50 g/day (SHR 0.39; 95% CI 0.21-0.73). A 50% reduction in mortality risk from other cancers was also noted for the highest consumption category (SHR 0.50; 95% CI 0.31-0.81). The findings support the beneficial role of EVOO in reducing cancer mortality, particularly with higher consumption levels. The results underscore EVOO's potential as a dietary intervention for cancer prevention, aligning with the Mediterranean diet's overall health benefits. Further research is needed to confirm these findings and explore the underlying mechanisms.

PDE models for vegetation biomass and autotoxicity

Numerical techniques are widely used to simulate population dynamics in space. In vegetation dynamics, these techniques are very useful to investigate how plants grow, compete for resources, and react to environmental factors within the ecosystem. Plant–soil feedback (PSF) refers to the process where plants or a community alter the biotic and abiotic characteristics of soil that affects the growth of plants or community subsequently growing in that soil. During the last three decades, PSF has been recognized as an important driver for the emergence of vegetation patterns. The importance of studying such vegetation patterns is that they provide an insight into potential ecological changes and illustrate the flexibility and resilience of an ecosystem. Despite the fact that water depletion was once thought to be a major factor in the development of vegetation patterns the existence of patterns in ecosystems without water limitations serves as evidence that this is not the case. In this study, we examine how negative plant–soil feedback contributes to the dynamics of plant biomass. We provide a comparison of different reaction–diffusion PDE models explaining the dynamics of plant biomass in the presence of autotoxicity produced by litter decomposition. We introduce different growth terms, including logistic and exponential, along with additional factors such as extra mortality and inhibitor terms, and develop six distinct models to investigate their individual and combined effects on biomass toxicity distribution. By applying appropriate numerical techniques, we solve the proposed reaction–diffusion PDE models in MATLAB to predict the impact of soil toxicity on plant biomass.

Impact of COVID-19 pandemic on care for chronic diseases in deprived and non-deprived neighbourhoods

Abstract Background Due to stringent lock-down measures imposed during COVID-19 pandemic the access to the primary care dropped significantly. This study aims to investigate the impact on GP consultations for diabetes mellitus (DM) and COPD during the pandemic. Methods In an observational study from January 2018-June 2022, anonymized medical records of 379.567 patients in Rotterdam, were analyzed for the impact on DM and COPD consultations during the lockdown (March-May 2020) and after the lockdown (June 2020-June 2022) compared to pre-pandemic levels. Results The study included 34.270 DM and 11.570 COPD patients. Until the COVID-19 pandemic, the patients living in deprived neighborhoods had comparisonly on average a higher number of consultations for DM (RR = 1.81, 95%CI=1.76-1.86) and COPD (RR = 1.48 95%CI=1.39-1.58). During the stringent lock-down there was almost same significant drop in both neighbourhoods in consultations for DM (RR = 0.85, 95%CI=0.79-0.92) and COPD (RR = 0.72, 95%CI=0.61-0.86). After the lockdown, the consultations for DM were higher and the HbA1c measurements were normalized compared to pre-pandemic levels in both neighbourhoods, (RR = 1.11, 95%CI=1.05-1.17) and (RR = 0.96, 95%CI=0.91-1.01) respectively. Conversely, the consultations for COPD and spirometry measurements remained significantly lower after the lockdown compared to pre-pandemic levels, (RR = 0.72, 95%CI=0.65-0.80) and (RR = 0.26, 95%CI=0.20-0.34) respectively. Surprisingly, the mean HbA1c value in the study population was significantly lower in the months after the lock-down (RR = 0.96, 95%CI=0.94-0.98) turning back to higher normal value at the end of 2021. Conclusions The recovery of primary care for chronic diseases after the lockdown phase was much faster for DM than for the COPD patients. The positive effect of lockdown on HbA1c was unfortunately temporary. More research is needed to know whether the decrease in chronic care has led to extra morbidity or mortality after 2 years of pandemic. Key messages • Diabetes mellitus’ care recovered soon for both deprived and non-deprived neighbourhoods after a significant drop during the lockdown. Lockdown seems to have a positive effect on disease management. • The significant delay in chronic care for COPD patients in both deprived and non-deprived neighbourhoods for almost two years, raises questions about the adverse health effects due to this delay.

Predictors associated with critical care need and in-hospital mortality among children with laboratory-confirmed COVID-19 infection in a high HIV infection burden region.

Despite the extra mortality associated with COVID-19 death globally, there is scant data on COVID-19-related paediatric mortality in Sub-Saharan Africa. We assessed predictors of critical care needs and hospital mortality in South African children with laboratory-confirmed SARS-CoV-2 infection in region with high HIV infection burden. We conducted a secondary multicentre analysis of the AFREhealth cohort (a multinational, multicentre cohort of paediatric COVID-19 clinical outcomes across six African countries) of children admitted to the Inkosi Albert Luthuli, a quaternary hospital in KwaZulu-Natal, South Africa, with confirmed RT-PCR between March 2020 and December 2020. We constructed multivariable logistic regression to explore factors associated with the need for critical care (high care/ intensive care hospitalisation or oxygen requirement) and cox-proportional hazards models to further assess factors independently associated with in-hospital death. Of the 82 children with PCR-confirmed SARS-CoV-2 infection (mean ± SD age: 4.2 ± 4.4 years), 35(42.7%) were younger than one year, 52(63%) were female and 59(71%) had a pre-existing medical condition. Thirty-seven (45.2%) children required critical care (median (IQR) duration: 7.5 (0.5-13.5) days) and 14(17%) died. Independent factors associated with need for critical care were being younger than 1 year (aPR: 3.02, 95%CI: 1.05-8.66; p = 0.04), having more than one comorbidity (aPR: 2.47, 95%CI: 1.32-4.61; p = 0.004), seizure (aPR: 2.39, 95%CI: 1.56-3.68; p < 0.001) and impaired renal function. Additionally, independent predictors of in-hospital mortality were exposure to HIV infection (aHR: 6.8, 95%CI:1.54-31.71; p = 0.01), requiring invasive ventilation (aHR: 3.59, 95%CI: 1.01-12.16, p = 0.048) and increase blood urea nitrogen (aHR: 1.06, 95%CI: 1.01-1.11; p = 0.017). However, children were less likely to die from COVID-19 if they were primarily admitted to quaternary unit (aHR: 0.23, 95%CI: 0.1-0.86, p = 0.029). We found a relatively high hospital death rate among children with confirmed COVID-19. During COVID-19 waves, a timely referral system and rapid identification of children at risk for critical care needs and death, such as those less than one year and those with comorbidities, could minimize excess mortality, particularly in high HIV-infection burden countries.

Risk of Mortality Associated with Preexisting Chronic Diseases and Prior Year Diagnosis of a Mental Disorder in Survivors of a First Myocardial Infarction or Stroke

Background: Chronic medical diseases and recurrent mental disorders are common and may lead to a negative prognosis in adults with cardiovascular diseases (CVDs). The impact of these overlapping morbidities is likely to be further increased in the critical years following a first acute CVD event such as a stroke or myocardial infarction (MI). Objectives: The objective of this study was to examine associations of preexisting chronic diseases and recent mental disorders with mortality in survivors of a first MI or stroke. Methods: Data from the 48,526 patients (59% men) aged ≥40 years with a first MI or stroke were extracted from the Quebec Integrated Chronic Disease Surveillance System. Cox regression models were used to assess the effect of preexisting cancer, renal disease, diabetes, chronic obstructive pulmonary disease (COPD), and recent mental disorders on the risk of recurrent fatal CVD events and all-cause mortality following the index MI or stroke. Results: An increased risk of CVD mortality was observed at 1, 3, and 4.5 years in women and men with coexisting mental disorders and at 4.5 years in those with chronic, preexisting renal disease. Inversely, cancer and COPD were associated with a lowered risk of CVD mortality during the study period. An increased risk of all-cause mortality at all time points was observed in adults with any of the assessed conditions. Conclusions: Adults with coexisting mental disorders are at increased risk of CVD mortality and all-cause mortality in the years following a first MI or stroke. This increased vulnerability is separate from the extra mortality attributable to preexisting chronic diseases.

Transition Intensities for Critical Illness: A Study on Canadian Health Data

Multiple state model is a mathematical model which is characterised by two important elements, transition intensity and transition probability. Critical illness has increased rapidly which is alarmed by the healthcare experts, and becoming an important concern in society. In this paper, by using the Canadian health data, we provide an estimation of transition intensities from the healthy state to the critical illness state with the application of prevalence rate. We provide a discrete calculation of transition intensities with some mathematical formula discussed by some previous studies. Next, we assume that the transition intensities of critical illnesses and death due to other causes are modelled by Gompertz and Makeham mortality models. We also compare and estimate the transition intensities of critical illnesses and dead due to other causes between these two models using a model selection method. We observe the sensitivity of the Gompertz and Makeham models with the different values of extra mortality . Lastly, we obtain and present the numerical results of the transition intensities of healthy lives to critical illness with the Canadian health data.

RETRACTED ARTICLE: Predictors of sternal wound infection post cardiac surgery in a Saudi Centre: a case control study

BackgroundSternal wound infection (SWI) post cardiac surgery remains an important cause of extra morbidity, mortality and cost. The objective was to identify risk factors for SWI in a cardiac centre in Eastern Saudi Arabia as part of the investigation into Surveillance variance in the local rates of SWI.MethodsWe included cases and controls from a cross section of patients who underwent major cardiac surgery between 2017 and 2020 matched for age, sex and time of surgery. An explanatory logistic regression model was fitted to estimate the risk factors.ResultsN = 204 (51 cases and 153 controls matching ratio 1:3, from a source population of 985 patients). factors significantly associated with SWI in the final multivariate model: hospital stay OR (1.05, Cl 1.01–1.10), Graft Conduit BIMA versus No Graft OR (10.94, Cl 1.60–74.63), transfusion of both packed cells plus other blood products versus no transfusion OR (3.53, Cl 93–13.44), HbA1c OR (1.09 Cl 0.84–1.41), BMI OR (1.25, Cl 1.04–1.50), perioperative blood glucose OR (1.02, Cl 1.004–1.03), surgery time OR (1.19, Cl 1.00–1.58).ConclusionsThe diverse aetiology, cross-disciplinary nature of SWI prevention, and despite improved prevention and control practices, including related care bundles with their proven value, SWI remain a serious challenge in cardiac surgery. Multidisciplinary consensus guidelines are well overdue.

PIT-tagging Italian spined loach (Cobitis bilineata): Methodology, survival and behavioural effects.

The Italian spined loach (Cobitis bilineata) is an elongated, small-sized (<12 cm) spined loach native to northern Italy, Slovenia and Croatia. As for loaches in general, little is known about the individual movements of this loach in nature. Passive integrated transponders (PIT-tags) are small (typically 7-32 mm), relatively cheap and allow tracking of individual fish movements and behaviour. A fundamental assumption in animal telemetry is that the performance of a tagged animal does not deviate substantially from its natural performance. Although PIT-tagged fish often display high survival and tag retention, the effect varies between species and contexts, and few studies have looked at behavioural effects of PIT-tagging. Here we demonstrate a PIT-tagging methodology for spined loaches, and compare survival, activity and provoked escape response (maximum swimming speed) between tagged and control fish. We also track tag retention in the tagged fish. Italian spined loaches tagged with 12 mm PIT-tags displayed high tag retention and no extra mortality, and no effects of tagging on activity or maximum swimming speed were observed. The tag-to-fish weight and length ratios in our study ranged from 2% to 5% and from 10% to 16%, respectively, and we conclude that PIT-tagging, within these ratios, appears suitable for Italian spined loach.

“Numberless Little Risks”: ‘Tropical Exposure’ in Globalizing Actuarial Discourse, 1852–1947

I argue that life insurance and imperial meaning making are deeply implicated in each other. As life insurance expanded internationally in the nineteenth century, and as insurers became advocates of White settlement, they grappled with what actuarial science meant in the context of their orientalist conceptions of colonial populations. In particular, actuaries were concerned with tropical markets and the racialized/exceptionalized differences they perceived in those markets. To address these tensions, insurers attempted two strategies: (1) incorporating tropical rates as additional premiums designed to cover the “extra mortality” of tropical markets; and (2) advocating for social practices of “sanitary progress” related to public health and sanitation. These practices, framed in orientalist terms, were not adopted in any smooth manner but in fumbling and meandering ways as insurers tried to understand what kinds of lives tropical settlers might be and how those lives might be priced. They eventually liberalized life insurance rates for White settlers in tropical settings, but insurers then confronted questions on how newly socialized “native” lives might be rendered calculable. This story of tropical exposure in globalizing actuarial discourse reinforces the ways in which race and racialized/exceptionalized differences were at the core of life insurance and the calculative devices it assembled between 1852 and 1947.

Predicting Demographic Indicators by Splines

The current demographic pattern in Ukraine features the decreasing birth rate and the increasing mortality, resulting in ageing and decline of the population, which breaks the favourable demographic balance. At the Ukrainian territories affected by radioactive contamination because of the accident at the Chornobyl nuclear power plant, these processes differ from those on other territories. Given the considerable impact of emergency situations on the course of demographic processes, developing and testing prediction techniques specifically designed for those territories has essential importance.&#x0D; The purpose of this work is to forecast changes in demographic indicators (population number, birth rate, mortality,infant mortality and stillbirth) by spline functions, forthe areas with the heaviest radioactive contamination after the Chornobyl disaster, which are located in Zhytomyr region (Korosten, Luhyno, Narodychy, Ovruch and Olevsk), for 2020–2023, and the town of Korosten for 2021–2023.The data sources for the research were State Statistic Service of Ukraine for 1979–2020, and the Ministry of Health of Ukraine for the period of the COVID-19 pandemic.&#x0D; At the first phase, spline functions were used to forecast the abovementioned indicators in 2017–2020 by data for 1979–2016 for the town of Korosten. A comparison of the resulting forecast with the actual data led to the conclusion that that spline models of observations could be an effective tool for short-term forecasting of population number, birth rate and mortality. The most adequate prediction of population numbers could be achieved with cubic splines, whereas the best prediction of birth rate and mortality – with linear continuous splines.&#x0D; The forecasts of birth and mortality rates for 2017–2020 proved to be quite optimistic. However, in the pandemic conditions, a deviation of the predicted population numbers, birth rate and mortality was revealed: actual numbers for all the three indicators in 2020 were beyond the confidence region, which had not been the case in 2017–2019. The actual figures in 2020, found to be far worse than the predicted ones, may be caused by the impact of the COVID-19 pandemic in 2020, which is an unpredictable factor. The extra mortality caused by COVID-19 in 2020 was estimated for the town of Korosten.&#x0D; At the second phase, probable changes in the population number, birth rate and mortality were predicted for 2021–2023 in all the areas. The 95% confidence region and confidence intervals were built for the predictions. It was found that the last years’ trends in demographic indicators in radioactively contaminated territories would continue in a short-term perspective. It was shown that because annual numbers of infant mortality and stillbirthcould not be predicted due to their significant variations, averaging for 5-year periods should be used.&#x0D; A forecast of the average numbers was made for the 5 five-year periods where actual data were unknown. Also, it was emphasized that for the indicators predicted with linear continuous splines, actual numbers might turn to be far from the forecasted ones, because of the existence of extreme points, with growth suddenly changing for decline, and vice versa. Because such points cannot be predicted by extrapolation of observed trends, it is necessary to find other methods for their prediction.&#x0D; Further research will focus on other prediction methods, to achieve higher prediction accuracy,and on inclusion of economic indicators in the prediction models.

Abstract P3-12-10: Socioeconomic status in young breast cancer patients is associated with inequalities in recurrence patterns: A population-based study in the Netherlands

Abstract Background Breast cancer survival is shown to be associated with socioeconomic status (SES), which is most pronounced in young patients. In this study, we investigated how consecutive recurrent events are associated with excess mortality according to SES in young breast cancer patients. Using detailed data on all recurrences that occur between date of diagnosis of the primary tumour and last observation, we provide a unique insight in the prognosis of young breast cancer patients according to SES. Methods All female patients &amp;lt;40 years with primary operated stage I-III breast cancer diagnosed in 2005 were selected from the Netherlands Cancer Registry. Data on all recurrences within 10 years from primary tumour diagnosis were collected directly from patient files. We analysed recurrence patterns according to SES, and estimated 10-year absolute risks of recurrence, contralateral breast cancer and mortality using cause-specific cumulative incidence functions, accounting for competing risks. Relationships between SES, recurrence patterns and excess mortality were estimated using a multivariable joint model, wherein the association between recurrent events and excess mortality (expected mortality derived from the general population) was included. Results We included 525 patients. Patients of high SES were more often diagnosed with stage II breast cancer as compared to patients of low and medium SES, who more often had stage I. In addition, patients of high SES more often had well differentiated tumours and HR+/HER2- disease as compared to low and medium SES, who more often were diagnosed with moderately or poorly differentiated tumours, HR-/HER2+ and HR-/HER2- disease. Local, regional and distant recurrence risks were higher in patients with low SES, lowest in patients with high SES. Death (n=6) and contralateral breast cancer (n=14) as first events were rare. The percentage of patients who died following a recurrence was 19.1% in low SES, compared to 15.3% and 13.2% in medium and high SES. Patients of low SES had more consecutive recurrences as compared to patients of high SES. In addition, they had shorter time intervals between diagnosis and first recurrence, and between first recurrence and death. In the joint model, adjusting for confounding, high SES was significantly related to lower 10-year recurrence rates, compared to low SES. Over the 10-year period, a strong association between the recurrence process and excess mortality was found. Conclusion This study shows that high SES is associated with a lower risk of 10-year recurrence overall, and less subsequent recurrent events, and that the pattern of recurrence is largely associated with the risk of extra mortality. Patients of low SES show a faster disease progression as compared to patients of high SES. Patients in the low socioeconomic group more often have HER-/HER2- disease, which suggests that there may be other breast cancer risk factors that play a role. Differences in treatment of recurrences were not assessed in this study and should be subject for further research, in order to further reduce socioeconomic differences. Citation Format: Marissa Corine van Maaren. Socioeconomic status in young breast cancer patients is associated with inequalities in recurrence patterns: A population-based study in the Netherlands [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-12-10.

Red Spot on the European Green Map: Will the Extra Catastrophic Phenomenon Take the Polish Poaching-Pressured Ospreys to the Brink of Extinction?

Simple SummaryScientific research is an integral part of species protection. Thanks to the use of camera monitoring during a conservation project targeting a threatened Polish population of Osprey, we discovered that the influence of natural causes of brood losses is stronger than in previous years. This would be a kind of catastrophe for the species in the whole country. We conclude that only active protection and stopping the anthropogenic causes of Osprey mortality (e.g., poaching) could stop the decline in the population and give Poland a chance to not to be red spot on the European green map of Osprey.Poland is the only European country where the Osprey population is declining due to the mortality of adult birds from poaching, which impacts not only single breeding attempts but also the Lifetime Reproductive Success (LRS) of specimens. However, what if there came an extra mortality factor in the moment of the lowest numbers of Osprey, already vulnerable in the country? In the years 2018–2020, we installed 22 trail cameras and five digital cameras (live online video feeds) on the nests. The total failure level observed in cameras (18.5%) was high. We observed, using these cameras, the extra mortality of chicks (10.7% of potentially fledged chicks) and even adult birds by unexpected predation by Northern Goshawk and White-tailed Eagle. This phenomenon is also common in the national population, as we found a total of ten cases of total losses by predators (eight or nine of them were birds of prey), including nests not covered by camera monitoring. The extra adult-predation by Goshawks means an extra drop in LRS. Those adult and chick predations are an example of exceptional catastrophic phenomena, which have been described as the direct cause of the extinction of animal populations throughout history. Only active conservation and stop poaching of the Polish population could stop the decline and save the Polish Ospreys.

A tritrophic interaction model for an olive tree pest, the olive moth — Prays oleae (Bernard)

The olive tree (Olea europaea L.) is among the oldest and most widespread crops in the Mediterranean basin. Portugal is the third olive producer in the European Union, and Trás-os-Montes region, located in northeastern Portugal, is the second Portuguese producing olive region.The olive moth, Prays oleae (Bernard) (Lepidoptera: Praydidae) is a key olive pest in Trás-os-Montes. This pest is a natural host/prey of several organisms which include larvae of generalist and specialist parasitoids as well as generalist predators and entomopathogens. Its most abundant parasitoid is the specialist Ageniaspis fuscicollis (Dalman) (Hymenoptera: Encyrtidae) and this, in Trás-os-Montes region, is commonly followed by the facultative hyperparasitoid Elasmus flabellatus (Fonscolombe) (Hymenoptera: Eulophidae). Spiders represent a relevant group of generalist predators in olive agroecosystems and encompass an important predatory action in agroecosystems as well as an ability to reduce the populations of various insect pests. In this context, a mathematical model, considering the population of the olive moth, the two parasitoids populations and the spider population as the variables in our system, was constructed. The ecosystem steady states for feasibility and stability were assessed. The possible pesticide effects, that represent essentially extra mortality rates for each one of the insect populations, and potential abundance variations on their populations under a climate change scenario were included. Results indicate that the most important natural control agent is A. fuscicollis but in certain conditions E. flabellatus or spiders may be relevant contributors for the pest reduction. This approach may provide a useful tool to assist the field researchers on this pest system and its management.

Spatial modelling of Lexis mortality data

In this work we present a spatial approach to investigate mortality data referenced over a Lexis structure. We decompose the force of mortality into two interpretable components: a Markov random field, homogeneous with respect to age, period and cohort which explains the main pattern of mortality; and a secondary component of independent shocks, accounting for additional non structured patterns. Inference is based on a hierarchical Bayesian model with Markov chain Monte Carlo computations. We present an application to data from the Human Mortality Database, with respect to Italy and Sweden, two countries with very different histories in terms of demographic and epidemiological transitions. For each country the primary surface of spatially structured mortality and the secondary surface of additional mortality are estimated. The importance of each component is evaluated by the estimated value of the respective precision parameter. In both Italy and Sweden, we discovered an interesting band of extra mortality in the secondary surface across the time domain, in the age interval between 60 and 90 years, with a slightly positive slope. The band represents a significant amount of extra mortality for the elderly population, which is otherwise incompatible with a structured dynamics in age, period and cohort.

Sjögren's Syndrome and Viral Infections.

Sjögren’s syndrome (SS) is a systemic autoimmune disease, characterized by lymphocytic infiltration of the secretory glands. This leads to dryness of the main mucosal surfaces such as the mouth, eyes, nose, larynx, pharynx, and vagina. Although there is little morbidity data at the initial diagnosis, SS may be a serious disease, with extra mortality caused by hematological cancer. The cause of SS is unknown, but factors postulated to play a role include genetic and environmental factors, hormonal abnormality, and viral infection. Under the influence of these factors, the immune system becomes abnormal and the tissue is damaged. In this study, we summarize recent developments in our understanding of the relationship between SS and viral infections, including Epstein–Barr virus (EBV), hepatitis C virus (HCV), human T cell lymphotropic virus type 1 (HTLV-1), cytomegalovirus (CMV), and human immunodeficiency virus (HIV).

A new cure model accounting for extra non-cancer mortality: Validation and application to real data

The proportion of cancer patients cured of the disease is estimated with standard cure models assuming they have the same risk of death as the general population [1] . These patients, however often maintain an extra risk of dying compared to the overall population, which we assume is due to other causes than cancer [2] . The aim of the work was to develop and validate an extended cure model incorporating the estimated patients’ relative risk of death from other causes (α) compared to that observed in the general population. We extended the mixture cure model considering Weibull relative survival of the uncured by including a relative risk αwhich muliptlies the mortality observed in the general population. The parameters were estimated using maximum likelihood method for individual data and unweighted least square for grouped data. The extended model was evaluated through a simulation study of the performance and robustness. The validity of parameters estimated by both the standard and the extended cure models was evaluated on a set of simulations based on scenarios mirroring the behavior of lung and breast cancer from real data with 1000 samples of different sizes (500–20,000 cases each), with different values of α, with different length of follow-up, with set-ups where all the assumptions are verified or where some of them are not verified (survival of uncured patients does not follow a Weibull distribution; extra non-cancer death risk is dependent of age at diagnosis or randomly varies across patients). The models were also applied to real data: colon cancer data from the FRANCIM common database. When the assumptions were satisfied, the extended cure models correctly estimated the parameters and their standard errors, providing excellent coverage, in all scenario. The standard model underestimated the proportion of cured by 7% when α = 1.2, and by 40% when α = 2.0. Age effect on the proportion of cured was heavily overestimated. Among the extended models, the maximum likelihood estimation on individual data outperformed the unweighted least square for grouped data. When some of the assumptions were violated, parameter estimates by both extended models appeared fairly robust. Applied to real colon cancer data (e.g. in men), the extended models estimated close values of α respectively 1.28 (95% confidence interval [1.16–1.40] for grouped data and 1.23 [1.12–1.35] for individual data) and cure fraction (respectively 57.2% [54.3–60.1%] and 55.7%[53.3–58.1%]), higher than that of the conventional model (51.0% [48.5–53.5%] for grouped data and 51.6% [50.0–53.3%] for individual data). In individual data analyses, AIC was smaller for the extended model (55748) than for the conventional model (55760). The present analysis suggests that conventional indicators overestimate cancer-specific death and underestimate cure fraction for cancer survivors. The extended models are more efficient to estimate net survival in presence of an extra risk of dying.

An eight-year multicenter study on short-term peripheral intravenous catheter-related bloodstream infection rates in 100 intensive care units of 9 countries in Latin America: Argentina, Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, Mexico, Panama, and Venezuela. Findings of the International Nosocomial Infection Control Consortium (INICC).

Data on short-term peripheral intravenous catheter-related bloodstream infections per 1,000 peripheral venous catheter days (PIVCR BSIs per 1,000 PVC days) rates from Latin America are not available, so they have not been thoroughly studied. International Nosocomial Infection Control Consortium (INICC) members conducted a prospective, surveillance study on PIVCR BSIs from January 2010 to March 2018 in 100 intensive care units (ICUs) among 41 hospitals, in 26 cities of 9 countries in Latin America (Argentina, Brazil, Colombia, Costa Rica, Dominican-Republic, Ecuador, Mexico, Panama, and Venezuela). The Centers for Disease Control and Prevention (CDC) National Health Safety Network (NHSN) definitions were applied, and INICC methodology and INICC Surveillance Online System software were used. In total, 10,120 ICU patients were followed for 40,078 bed days and 38,262 PVC days. In addition, 79 PIVCR BSIs were identified, with a rate of 2.06 per 1,000 PVC days (95% confidence interval [CI], 1.635-2.257). The average length of stay (ALOS) of patients without a PIVCR BSI was 3.95 days, and the ALOS was 5.29 days for patients with a PIVCR BSI. The crude extra ALOS was 1.34 days (RR, 1.33; 95% CI, 1.0975-1.6351; P = .040).The mortality rate in patients without PIVCR BSI was 3.67%, and this rate was 6.33% in patients with a PIVCR BSI. The crude extra mortality was 1.70 times higher. The microorganism profile showed 48.5% gram-positive bacteria (coagulase-negative Staphylococci 25.7%) and 48.5% gram-negative bacteria: Acinetobacter spp, Escherichia coli, and Klebsiella spp (8.5% each one), Pseudomonas aeruginosa (5.7%), and Candida spp (2.8%). The resistances of Pseudomonas aeruginosa were 0% to amikacin and 50% to meropenem. The resistance of Acinetobacter baumanii to amikacin was 0%, and the resistance of coagulase-negative Staphylococcus to oxacillin was 75%. Our PIVCR BSI rates were higher than rates from more economically developed countries and were similar to those of countries with limited resources.

Modeling size-density trajectories of even-aged ash (Fraxinus excelsior L.) stands in France. A baseline to assess the impact of Chalara ash dieback

A piecewise polynomial function already used to represent the size-density trajectories of pure even-aged stands of beech, oak, and Douglas-fir proved its ability to represent the size-density trajectories of a new species, ash. The widespread ash dieback caused departures from the expected size-density trajectories. These abnormalities can be used to detect an extra level of mortality due to infection by Hymenoscyphus fraxineus in pure even-aged ash stands. The size-density trajectories allow quantifying more precisely the density of stands and can help the forest manager to decide of the opportunity of thinnings. This study helped to quantify extra mortality in pure even-aged stands by using the size-density trajectories established for stands evolving at maximum density. This study was conducted to establish size-density trajectories of pure even-aged ash stands and compare them with those recently established for beech and oak in France, in particular concerning the onset of density-dependent (regular) mortality. The additional effect of ash dieback on mortality was also an issue. We used permanent and semi-permanent unthinned ash plots installed in the north of France and where inventories of trees were performed at more or less regular intervals: measurements included tree status (dead or alive) and diameter or girth at breast height for all trees and total height for a sample of living trees. The size-density trajectories of plots describing the course of the number of living trees in relation with the mean stand girth, in logarithmic scales, were modeled with a piecewise polynomial function fitted with a mixed-effects model. A permanent sample of trees was also selected for ash dieback and extra mortality monitoring. The piecewise polynomial function already used proved its ability to represent the size-density trajectories of even-aged ash stands of various initial densities and fertility levels. As for beech and oak, the trajectories were modeled so that mortality onset occurred at a constant relative density. This level appeared to be much higher for ash (RDI = 0.58), revealing that ash survived with less growing space than beech and oak and appeared to be more efficient. Ash dieback caused an additional mortality in the experimental ash stands studied, and this excess of mortality appeared predictable on the basis of observed departures from the expected size-density trajectories. A single parameter function family could be used to predict the size-density trajectories of even-aged ash stands, on the basis of the results obtained previously on oak and beech. Mortality onset and space requirements of ash could be compared with those of beech and oak and show that ash can survive at higher densities and is a more efficient species. Predicted size-density trajectories proved also useful to detect and quantify the excess of mortality due to H. fraxineus on ash. This approach could be extended to other diseases and species with predictable size-density trajectories.

Contributions of power generation to air pollution and associated health risks in India: Current status and control scenarios

Coal based power plants are the biggest source of air pollution from power sector and thus it becomes imperative to study its contribution to air pollution in India. This study estimates impact of power generation on pollutant concentrations and associated mortality across India in current scenario and compares with three other control policy intervention scenarios in 2015. About 60% of total power generated in India in 2015 was from coal fired plants which contributed to about 49%, 34%, 6.6% & 6% of SO2, NOx, PMfine and CO emissions in India. Contribution of power plants to fine particulate matter (PM2.5) was the highest in winter (14.12 μg/m3) and lowest in monsoon (1.99 μg/m3). SO4− and NO3− contributed the most (65%–97%) to total PM2.5 attributed to power plants indicating maximum reduction in secondary inorganic aerosols due to implementation of regulating policies on power plants. Among the 3 control policy intervention scenarios on power plants, COPP scenario reflecting implementation of emission standards on current operating plants, was found to be the best scenario resulting in reduction of pollutant concentrations. It resulted in reduction of about 9 μg/m3 in PM2.5 concentration which in turn lead to 73,209 lives saved and increase in about 1.7 Years of life lost/person (YLL/person). On the other hand, in case of UCPP and CNPP scenarios where regulating policies were implemented only in under construction and new power plants respectively resulted in increased PM2.5 concentration of about 8.22 μg/m3 and 19.03 μg/m3 and also 50,200 and 1,15,894 extra premature mortality.

Can the creation of new freshwater habitat demographically offset losses of Pacific salmon from chronic anthropogenic mortality?

Over 1 billion USD are devoted annually to rehabilitating freshwater habitats to improve survival for the recovery of endangered salmon populations. Mitigation often requires the creation of new habitat (e.g. habitat offsetting) to compensate population losses from human activities, however offsetting schemes are rarely evaluated. Anadromous Pacific salmon are ecologically, culturally, and economically important in the US and Canada, and face numerous threats from degradation of freshwater habitats. Here we used a matrix population model of coho salmon (Oncorhynchus kisutch) to determine the amount of habitat offsetting needed to compensate mortality (2-20% per year) caused by a range of development activities. We simulated chronic mortality to three different life stages (egg, parr, smolt/adult), individually and simultaneously, to mimic impacts from development, and evaluated if the number of smolts produced from constructed side-channels demographically offset losses. We show that under ideal conditions, the typical size of a constructed side-channel in the Pacific Northwest (PNW) (3405 m2) is sufficient to compensate for only relatively low levels of chronic mortality to either the parr or smolt/adult stages (2-7% per year), but populations do not recover if mortality is >10% per year. When we assumed lower productivity (e.g.; 25th percentile), we found that constructed channels would need to be 2.5-4.5 fold larger as compared to the typical size built in the PNW, respectively, to maintain population sizes. Moreover, when we imposed mortality to parr and smolt/adult stages simultaneously, we found that constructed side-channels would need to be between 1.8- and 2.3- fold larger that if the extra chronic mortality was imposed to one life stage only. We conclude that habitat offsetting has the potential to mitigate chronic mortality to early life stages, but that realistic assumptions about productivity of constructed side-channels and cumulative effects of anthropogenic disturbances on multiple life stages need to be considered.