scholarly journals Co-infections determine patterns of mortality in a population exposed to parasite infection

2015 ◽  
Vol 1 (2) ◽  
pp. e1400026 ◽  
Author(s):  
Mark E. J. Woolhouse ◽  
Samuel M. Thumbi ◽  
Amy Jennings ◽  
Margo Chase-Topping ◽  
Rebecca Callaby ◽  
...  

Many individual hosts are infected with multiple parasite species, and this may increase or decrease the pathogenicity of the infections. This phenomenon is termed heterologous reactivity and is potentially an important determinant of both patterns of morbidity and mortality and of the impact of disease control measures at the population level. Using infections withTheileria parva(a tick-borne protozoan, related toPlasmodium) in indigenous African cattle [where it causes East Coast fever (ECF)] as a model system, we obtain the first quantitative estimate of the effects of heterologous reactivity for any parasitic disease. In individual calves, concurrent co-infection with less pathogenic species ofTheileriaresulted in an 89% reduction in mortality associated withT. parvainfection. Across our study population, this corresponds to a net reduction in mortality due to ECF of greater than 40%. Using a mathematical model, we demonstrate that this degree of heterologous protection provides a unifying explanation for apparently disparate epidemiological patterns: variable disease-induced mortality rates, age-mortality profiles, weak correlations between the incidence of infection and disease (known as endemic stability), and poor efficacy of interventions that reduce exposure to multiple parasite species. These findings can be generalized to many other infectious diseases, including human malaria, and illustrate how co-infections can play a key role in determining population-level patterns of morbidity and mortality due to parasite infections.

Vaccines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1180
Author(s):  
Tinevimbo Shiri ◽  
Marc Evans ◽  
Carla A. Talarico ◽  
Angharad R. Morgan ◽  
Maaz Mussad ◽  
...  

Debate persists around the risk–benefit balance of vaccinating adolescents and children against COVID-19. Central to this debate is quantifying the contribution of adolescents and children to the transmission of SARS-CoV-2, and the potential impact of vaccinating these age groups. In this study, we present a novel SEIR mathematical disease transmission model that quantifies the impact of different vaccination strategies on population-level SARS-CoV-2 infections and clinical outcomes. The model employs both age- and time-dependent social mixing patterns to capture the impact of changes in restrictions. The model was used to assess the impact of vaccinating adolescents and children on the natural history of the COVID-19 pandemic across all age groups, using the UK as an example. The base case model demonstrates significant increases in COVID-19 disease burden in the UK following a relaxation of restrictions, if vaccines are limited to those ≥18 years and vulnerable adolescents (≥12 years). Including adolescents and children in the vaccination program could reduce overall COVID-related mortality by 57%, and reduce cases of long COVID by 75%. This study demonstrates that vaccinating adolescents and children has the potential to play a vital role in reducing SARS-CoV-2 infections, and subsequent COVID-19 morbidity and mortality, across all ages. Our results have major global public health implications and provide valuable information to inform a potential pandemic exit strategy.


2021 ◽  
Vol 26 (40) ◽  
Author(s):  
Jessica E Stockdale ◽  
Renny Doig ◽  
Joosung Min ◽  
Nicola Mulberry ◽  
Liangliang Wang ◽  
...  

Background Many countries have implemented population-wide interventions to control COVID-19, with varying extent and success. Many jurisdictions have moved to relax measures, while others have intensified efforts to reduce transmission. Aim We aimed to determine the time frame between a population-level change in COVID-19 measures and its impact on the number of cases. Methods We examined how long it takes for there to be a substantial difference between the number of cases that occur following a change in COVID-19 physical distancing measures and those that would have occurred at baseline. We then examined how long it takes to observe this difference, given delays and noise in reported cases. We used a susceptible-exposed-infectious-removed (SEIR)-type model and publicly available data from British Columbia, Canada, collected between March and July 2020. Results It takes 10 days or more before we expect a substantial difference in the number of cases following a change in COVID-19 control measures, but 20–26 days to detect the impact of the change in reported data. The time frames are longer for smaller changes in control measures and are impacted by testing and reporting processes, with delays reaching ≥ 30 days. Conclusion The time until a change in control measures has an observed impact is longer than the mean incubation period of COVID-19 and the commonly used 14-day time period. Policymakers and practitioners should consider this when assessing the impact of policy changes. Rapid, consistent and real-time COVID-19 surveillance is important to minimise these time frames.


Parasitology ◽  
1985 ◽  
Vol 91 (2) ◽  
pp. 317-347 ◽  
Author(s):  
A. P. Dobson

A number of published studies of competition between parasite species are examined and compared. It is suggested that two general levels of interaction are discernible: these correspond to the two levels of competition recognized by workers studying free-living animals and plants: ‘exploitation’ and ‘interference’ competition. The former may be defined as the joint utilization of a host species by two or more parasite species, while the latter occurs when antagonistic mechanisms are utilized by one species either to reduce the survival or fecundity of a second species or to displace it from a preferred site of attachment. Data illustrating both levels of interaction are collated from a survey of the published literature and these suggest that interference competition invariably operates asymmetrically. The data are also used to estimate a number of population parameters which are important in determining the impact of competition at the population level. Theoretical models of host-parasite associations for both classes of competition are used to examine the expected patterns of population dynamics that will be exhibited by simple two-species communities of parasites that utilize the same host population. The analysis suggests that the most important factor allowing competing species of parasites to coexist is the statistical distribution of the parasites within the host population. A joint stable equilibrium should be possible if both species are aggregated in their distribution. The size of the parasite burdens at equilibrium is then determined by other life-history parameters such as pathogenicity, rates of resource utilization and antagonistic ability. Comparison of these theoretical expectations with a variety of sets of empirical data forms the basis for a discussion about the importance of competition in natural parasite populations. The models are used to assess quantitatively the potential for using competing parasite species as biological control agents for pathogens of economic or medical importance. The most important criterion for identifying a successful control agent is an ability to infect a high proportion of the host population. If such a parasite species also exhibits an intermediate level of pathology or an efficient ability to utilize shared common resources, antagonistic interactions between the parasite species contribute only secondarily to the success of the control. Competition in parasites is compared with competition in free-living animals and plants. The comparison suggests further experimental tests which may help to assess the importance of competition in determining the structure of more complex parasite-host communities.


2021 ◽  
Author(s):  
Andrew J. Shattock ◽  
Epke A. Le Rutte ◽  
Robert P Duenner ◽  
Swapnoleena Sen ◽  
Sherrie L Kelly ◽  
...  

As vaccination coverage against SARS-CoV-2 increases amidst the emergence and spread of more infectious and potentially more deadly viral variants, decisions on timing and extent of relaxing effective, but unsustainable, non-pharmaceutical interventions (NPIs) need to be made. An individual-based transmission model of SARS-CoV-2 dynamics, OpenCOVID, was developed to compare the impact of various vaccination and NPI strategies on the COVID-19 epidemic in Switzerland. We estimate that any relaxation of NPIs in March 2021 will lead to increasing cases, hospitalisations, and deaths resulting in a "third wave" in spring and into summer 2021. However, we find a cautious phased relaxation can substantially reduce population-level morbidity and mortality. We find that faster vaccination campaign can offset the size of such a wave, allowing more flexibility for NPI to be relaxed sooner. Our sensitivity analysis revealed that model results are particularly sensitive to the infectiousness of variant B.1.1.7.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 5017-5017
Author(s):  
Dave Smart ◽  
Wendy Moore ◽  
Karina Hjort ◽  
Karen Keating ◽  
Bob Holt ◽  
...  

Abstract Introduction Measures taken to mitigate infection spread during the 2020 COVID-19 pandemic are considered to have caused significant unintended consequences on other diseases. Large decreases in the numbers of symptomatic and asymptomatic people presenting for diagnosis of heart disease, diabetes and cancer have been observed. A recent analysis of solid tumors showed up to 70% reduction in the number of patients presenting for diagnosis. The potential exists for significantly increased morbidity and mortality for these missed or delayed presenting patients. Further, it is important to determine whether infection spread mitigation measures affected the diagnostic testing and treatment decisions for these patients. This study aimed to determine whether pandemic control measures affected presentation, testing and treatment of patients across eight different hematologic cancers. Methods CMS claims data were analyzed for the presence of diagnostic (DX) ICD 10 codes indicative of hematologic cancer. Patients with a DX code first appearing in 2019 or in 2020 were selected to provide newly diagnosed pre-COVID-19 and during COVID-19 cohorts for comparison, with unique patient counts being calculated for each month. A "COVID-19 dip" i.e. a decrease in the number of patients was calculated as the change in number of patients diagnosed in a given month relative to the number for JAN2020. Dip duration was calculated only when the decrease was >10% of the JAN2020 figure. Patients who received treatment via a "J" code Healthcare Common Procedure Coding System (HCPCS) code were extracted from the cohorts and the time taken from initial diagnosis to first treatment calculated. Results Eight hematologic cancers: AML, CLL, CML, HEME (a group of different hematologic cancers), Hodgkins (HOG), Myelodysplasia (MDS), Non-Follicular Lymphomas (NFL), and Non-Hodgkins Lymphoma (NHL) showed a decrease in the number of patients being diagnosed during the early part of 2020 (Fig.1) Fig.1. Change in new patient diagnoses for selected hematologic cancers as a proportion of their JAN2020 value There was some variation in the depth and duration of the COVID-19 dip (Table 1) with MDS having both the longest and deepest dip. Median depth and duration of the dip was 33% and 3.5 months, respectively, with all dips starting either in FEB or MAR2020. Table 1. Duration and depth of COVID-19 dips for selected hematological cancers The proportions of patients receiving therapy via J HCPCS code (JRX) are shown in Table 2 Table 2. Proportions of patients receiving J code therapy Conclusions The decline in new patient diagnoses for heme cancers during the period when COVID-19 control measures were implemented is similar to that seen with solid tumors, although the depth of the COVID-19 dip was generally larger in the latter. There is no evidence of "catch up" diagnosis occurring i.e. patients missing from Q2 2020 are not reappearing en masse in subsequent quarters. The decline for MDS patients has, except for SEP to OCT2020, remained. Collectively, (depending on the calculation method), the COVID-19 dip for these eight heme cancers represents 16,584-33,671 patients who will likely have significantly increased rates of morbidity and mortality due to delayed diagnosis. Analysis of J code treatments show little difference between the proportions of patients receiving these treatments in 2020 compared to 2019 suggesting that at least some aspects of treatment e.g. infused chemotherapy, IO drugs for these patients was relatively unchanged by pandemic control measures. It also suggests that the main cause for decreased patient numbers treated is due to decreased testing for diagnosis, rather than not being treated once diagnosed. This aligns with findings from studies in the US and UK. The results of this study indicate that there may be a "backlog" of tens of thousands of people with cancer whose diagnosis has been significantly delayed and who urgently need to be identified in order to get on proper treatment to lessen the impact of that delay. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12566
Author(s):  
Matthieu Domenech de Cellès ◽  
Jean-Sebastien Casalegno ◽  
Bruno Lina ◽  
Lulla Opatowski

As in past pandemics, co-circulating pathogens may play a role in the epidemiology of coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In particular, experimental evidence indicates that influenza infection can up-regulate the expression of ACE2—the receptor of SARS-CoV-2 in human cells—and facilitate SARS-CoV-2 infection. Here we hypothesized that influenza impacted the epidemiology of SARS-CoV-2 during the early 2020 epidemic of COVID-19 in Europe. To test this hypothesis, we developed a population-based model of SARS-CoV-2 transmission and of COVID-19 mortality, which simultaneously incorporated the impact of non-pharmaceutical control measures and of influenza on the epidemiological dynamics of SARS-CoV-2. Using statistical inference methods based on iterated filtering, we confronted this model with mortality incidence data in four European countries (Belgium, Italy, Norway, and Spain) to systematically test a range of assumptions about the impact of influenza. We found consistent evidence for a 1.8–3.4-fold (uncertainty range across countries: 1.1 to 5.0) average population-level increase in SARS-CoV-2 transmission associated with influenza during the period of co-circulation. These estimates remained robust to a variety of alternative assumptions regarding the epidemiological traits of SARS-CoV-2 and the modeled impact of control measures. Although further confirmatory evidence is required, our results suggest that influenza could facilitate the spread and hamper effective control of SARS-CoV-2. More generally, they highlight the possible role of co-circulating pathogens in the epidemiology of COVID-19.


2020 ◽  
Author(s):  
Jessica E Stockdale ◽  
Renny Doig ◽  
Joosung Min ◽  
Nicola Mulberry ◽  
Liangliang Wang ◽  
...  

AbstractBackgroundMany countries have implemented population-wide interventions such as physical distancing measures, in efforts to control COVID-19. The extent and success of such measures has varied. Many jurisdictions with declines in reported COVID-19 cases are moving to relax measures, while others are continuing to intensify efforts to reduce transmission.AimWe aim to determine the time frame between a change in COVID-19 measures at the population level and the observable impact of such a change on cases.MethodsWe examine how long it takes for there to be a substantial difference between the cases that occur following a change in control measures and those that would have occurred at baseline. We then examine how long it takes to detect a difference, given delays and noise in reported cases. We use changes in population-level (e.g., distancing) control measures informed by data and estimates from British Columbia, Canada.ResultsWe find that the time frames are long: it takes three weeks or more before we might expect a substantial difference in cases given a change in population-level COVID-19 control, and it takes slightly longer to detect the impacts of the change. The time frames are shorter (11-15 days) for dramatic changes in control, and they are impacted by noise and delays in the testing and reporting process, with delays reaching up to 25-40 days.ConclusionThe time until a change in broad control measures has an observed impact is longer than is typically understood, and is longer than the mean incubation period (time between exposure than onset) and the often used 14 day time period. Policy makers and public health planners should consider this when assessing the impact of policy change, and efforts should be made to develop rapid, consistent real-time COVID-19 surveillance.


Author(s):  
Mihail Zver'kov

To the article the results of the theoretical and experimental researches are given on questions of estimates of the dynamic rate effect of raindrop impact on soil. The aim of this work was to analyze the current methods to determine the rate of artificial rain pressure on the soil for the assessment of splash erosion. There are the developed author’s method for calculation the pressure of artificial rain on the soil and the assessment of splash erosion. The study aims to the justification of evaluation methods and the obtaining of quantitative characteristics, prevention and elimination of accelerated (anthropogenic) erosion, the creation and the realization of the required erosion control measures. The paper considers the question of determining the pressure of artificial rain on the soil. At the moment of raindrops impact, there is the tension in the soil, which is called vertical effective pressure. It is noted that the impact of rain drops in the soil there are stresses called vertical effective pressure. The equation for calculation of vertical effective pressure is proposed in this study using the known spectrum of raindrops. Effective pressure was 1.4 Pa for the artificial rain by sprinkler machine «Fregat» and 5.9 Pa for long distance sprinkler DD-30. The article deals with a block diagram of the sequence for determining the effective pressure of rain drops on the soil. This diagram was created by the author’s method of calculation of the effective pressure of rain drops on the soil. The need for an integrated approach to the description of the artificial rain impact on the soil is noted. Various parameters characterizing drop erosion are considered. There are data about the mass of splashed soil in the irrigation of various irrigation machinery and installations. For example, the rate (mass) of splashed soil was 0.28…0.78 t/ha under irrigation sprinkler apparatus RACO 4260–55/701C in the conditions of the Ryazan region. The method allows examining the environmental impact of sprinkler techniques for analyzes of the pressure, caused by raindrops, on the soil. It can also be useful in determining the irrigation rate before the runoff for different types of sprinkler equipment and soil conditions.


2019 ◽  
Vol 10 (12) ◽  
pp. 1183-1199
Author(s):  
Mohammed Alrouili ◽  

This study attempted to identify the impact of internal work environment on the retention of healthcare providers at Turaif General Hospital in the Kingdom of Saudi Arabia. In particular, the study aimed to identify the dimensions of work circumstances, compensation, and relationship with colleagues, professional growth, and the level of healthcare providers’ retention. In order to achieve the study goals, the researcher used the descriptive analytical approach. The researcher used the questionnaire as the study tool. The study population comprised all the healthcare providers at Turaif General Hospital. Questionnaires were distributed to the entire study sample that consisted of 220 individuals. The number of questionnaires valid for study was 183 questionnaires. The research findings were as follows: the participants’ estimate of the work circumstances dimension was high (3.64), the participants’ estimate of the compensation dimension was moderate (3.32), the participants’ estimate of the relationship with colleagues dimension was high (3.62), the participants’ estimate of the professional growth dimension was weak (2.39), and the participants’ estimate of healthcare providers’ retention level was intermediate (2.75). Accordingly, the researcher’s major recommendations are: the need to create the right atmosphere for personnel in hospitals, the interest of the hospital to provide the appropriate conditions for the staff in terms of the physical and moral aspects for building the work adjustment in the staff, and conducting training courses and educational lectures for personnel in hospitals on how to cope with the work pressures.


2019 ◽  
Vol 13 (2) ◽  
Author(s):  
Arief Hidayatullah Khamainy ◽  
Dessy Novitasari Laras Asih

The research was carried out to find the influence of training material and methods of training toward workability. The study was conducted respectively from an employee of PD BPR Bantul Yogyakarta. The purpose of this research is expected to be useful for stakeholders in seeing CSR disclosure in the company in testing and analyzing its effect on the company's financial performance and with the presence of anti-corruption exposure, whether it will strengthen the impact of CSR disclosure on the company's financial performance. The study population in this study were all mining companies registered on the Indonesia Stock Exchange in 2016-2018 with a total of 63 companies. The research sample was taken using a random sampling technique that was calculated by the Slovin formula so that 54 samples were obtained for analysis. Linear Regression Analysis and Moderation Regression Analysis were chosen as the analysis technique used in this study. The results show that CSR disclosure does not affect the company's financial performance, and anti-corruption disclosure does not affect the relationship between the two.


Sign in / Sign up

Export Citation Format

Share Document