scholarly journals Heterogeneity in transmission parameters of hookworm infection within the baseline data from the TUMIKIA study in Kenya

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
James E. Truscott ◽  
Alison K. Ower ◽  
Marleen Werkman ◽  
Katherine Halliday ◽  
William E. Oswald ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Positive Association ◽  
Monitoring And Evaluation ◽  
Host Population ◽  
Transmission Model ◽  
High Coverage ◽  
Study Region ◽  
Transmission Parameters ◽  
Parasite Aggregation ◽  
The Impact

Abstract Background As many countries with endemic soil-transmitted helminth (STH) burdens achieve high coverage levels of mass drug administration (MDA) to treat school-aged and pre-school-aged children, understanding the detailed effects of MDA on the epidemiology of STH infections is desirable in formulating future policies for morbidity and/or transmission control. Prevalence and mean intensity of infection are characterized by heterogeneity across a region, leading to uncertainty in the impact of MDA strategies. In this paper, we analyze this heterogeneity in terms of factors that govern the transmission dynamics of the parasite in the host population. Results Using data from the TUMIKIA study in Kenya (cluster STH prevalence range at baseline: 0–63%), we estimated these parameters and their variability across 120 population clusters in the study region, using a simple parasite transmission model and Gibbs-sampling Monte Carlo Markov chain techniques. We observed great heterogeneity in R0 values, with estimates ranging from 1.23 to 3.27, while k-values (which vary inversely with the degree of parasite aggregation within the human host population) range from 0.007 to 0.29 in a positive association with increasing prevalence. The main finding of this study is the increasing trend for greater parasite aggregation as prevalence declines to low levels, reflected in the low values of the negative binomial parameter k in clusters with low hookworm prevalence. Localized climatic and socioeconomic factors are investigated as potential drivers of these observed epidemiological patterns. Conclusions Our results show that lower prevalence is associated with higher degrees of aggregation and hence prevalence alone is not a good indicator of transmission intensity. As a consequence, approaches to MDA and monitoring and evaluation of community infection status may need to be adapted as transmission elimination is aimed for by targeted treatment approaches.

Parasite infection and host dynamics in a naturally fluctuating rodent population

2012 ◽  
Vol 90 (9) ◽  
pp. 1149-1160 ◽  
Author(s):  
J.C. Winternitz ◽  
M.J. Yabsley ◽  
S.M. Altizer
Keyword(s):  
Population Density ◽  
Experimental Studies ◽  
Host Density ◽  
Positive Association ◽  
Population Cycles ◽  
Host Population ◽  
Reproductive Status ◽  
Vole Cycles ◽  
Host Infection ◽  
The Impact

Parasites can both influence and be affected by host population dynamics, and a growing number of case studies support a role for parasites in causing or amplifying host population cycles. In this study, we examined individual and population predictors of gastrointestinal parasitism on wild cyclic montane voles ( Microtus montanus (Peale, 1848)) to determine if evidence was consistent with theory implicating parasites in population cycles. We sampled three sites in central Colorado for the duration of a multiannual cycle and recorded the prevalence and intensity of directly transmitted Eimeria Schneider, 1875 and indirectly transmitted cestodes from a total of 267 voles. We found significant associations between host infection status, individual traits (sex, age, and reproductive status) and population variables (site, trapping period, and population density), including a positive association between host density and cestode prevalence, and a negative association between host density and Eimeria prevalence. Both cestode and Eimeria intensity correlated positively with host age, reproductive status, and population density, but neither parasite was associated with poorer host condition. Our findings suggest that parasites are common in this natural host, but determining their potential to influence montane vole cycles requires future experimental studies and long-term monitoring to determine the fitness consequences of infection and the impact of parasite removal on host dynamics.

Modelling patterns of parasite aggregation in natural populations: trichostrongylid nematode–ruminant interactions as a case study

Parasitology ◽  
1995 ◽  
Vol 111 (S1) ◽  
pp. S135-S151 ◽  
Author(s):  
B. T. Grenfell ◽  
K. Wilson ◽  
V. S. Isham ◽  
H. E. G. Boyd ◽  
K. Dietz
Keyword(s):  
Population Biology ◽  
Negative Binomial ◽  
Natural Populations ◽  
Parasite Load ◽  
Host Immunity ◽  
Moment Closure ◽  
The Mean ◽  
Parasite Aggregation ◽  
The Impact ◽  
The Relationship

SUMMARYThe characteristically aggregated frequency distribution of macroparasites in their hosts is a key feature of host–parasite population biology. We begin with a brief review of the theoretical literature concerning parasite aggregation. Though this work has illustrated much about both the sources and impact of parasite aggregation, there is still no definitive analysis of both these aspects. We then go on to illustrate the use of one approach to this problem – the construction of Moment Closure Equations (MCEs), which can be used to represent both the mean and second moments (variances and covariances) of the distribution of different parasite stages and phenomenological measures of host immunity. We apply these models to one of the best documented interactions involving free-living animal hosts – the interaction between trichostrongylid nematodes and ruminants. The analysis compares patterns of variability in experimental infections of Teladorsagia circumcincta in sheep with the equivalent wildlife situation – the epidemiology of T. circumcincta in a feral population of Soay sheep on St Kilda, Outer Hebrides. We focus on the relationship between mean parasite load and aggregation (inversely measured by the negative binomial parameter, k) for cohorts of hosts. The analysis and empirical data indicate that k tracks the increase and subsequent decline in the mean burden with host age. We discuss this result in terms of the degree of heterogeneity in the impact of host immunity or parasite-induced mortality required to shorten the tail of the parasite distribution (and therefore increase k) in older animals. The model is also used to analyse the relationship between estimated worm and egg counts (since only the latter are often available for wildlife hosts). Finally, we use these results to review directions for future work on the nature and impact of parasite aggregation.

The relationship between citations, downloads and alternative metrics in rheumatology publications: a bibliometric study

Rheumatology ◽  
2019 ◽  
Vol 59 (2) ◽  
pp. 277-280 ◽  
Author(s):  
Winnie M Y Chen ◽  
Marwan Bukhari ◽  
Francesca Cockshull ◽  
James Galloway
Keyword(s):  
Negative Binomial ◽  
Positive Association ◽  
Negative Binomial Regression ◽  
Significant Positive Association ◽  
H Index ◽  
Binomial Regression ◽  
Number Of Citations ◽  
The Impact ◽  
The Relationship ◽  
Alternative Metrics

Abstract Objective Scientific journals and authors are frequently judged on ‘impact’. Commonly used traditional metrics are the Impact Factor and H-index. However, both take several years to formulate and have many limitations. Recently, Altmetric—a metric that measures impact in a non-traditional way—has gained popularity. This project aims to describe the relationships between subject matter, citations, downloads and Altmetric within rheumatology. Methods Data from publications in Rheumatology were used. Articles published from 2010 to 2015 were reviewed. Data were analysed using Stata 14.2 (StataCorp, College Station, TX, USA). Correlation between citations, downloads and Altmetric were quantified using linear regression, comparing across disease topics. Relationship between downloads and months since publications were described using negative binomial regression, clustering on individual articles. Results A total of 1460 Basic Science and Clinical Science articles were identified, with the number of citations, downloads and Altmetric scores. There were no correlations between disease topic and downloads (R2 = 0.016, P = 0.03), citations (R2 = 0.011, P = 0.29) or Altmetric (R2 = 0.025, P = 0.02). A statistically significant positive association was seen between the number of citations and downloads (R2 = 0.29, P < 0.001). No correlations were seen between Altmetric and downloads (R2 = 0.028, P < 0.001) or citations (R2 = 0.004, P = 0.445). Conclusion Disease area did not correlate with any of the metrics compared. Correlations were apparent with clear links between downloads and citations. Altmetric identified different articles as high impact compared with citation or download metrics. In conclusion: tweeting about your research does not appear to influence citations.

Modeling impulsive resource inputs in host–parasitoid interactions with time delays

2018 ◽  
Vol 11 (05) ◽  
pp. 1850064 ◽  
Author(s):  
Shouzong Liu ◽  
Mingzhan Huang ◽  
Xinyu Song ◽  
Shuai Li ◽  
Huidong Cheng
Keyword(s):  
Negative Binomial ◽  
Fixed Point Theory ◽  
Stage Structure ◽  
Positive Periodic Solution ◽  
Point Theory ◽  
Host Population ◽  
Laboratory Environment ◽  
Total Input ◽  
Adult Parasitoid ◽  
The Impact

For the interaction of parasitoids and their insect hosts in the laboratory environment, a novel mathematical model with impulsive resource inputs, stage-structure, maturation delays and negative binomial distribution is proposed. Based on the adaptability of the insect host to the environment, we study the permanence of the system in two cases and gain conditions under which the host and parasitoid species can coexist with impulsive resource inputs. We also discuss the existence of the positive periodic solution when the system is permanent by applying a fixed point theory. Besides, we perform numerical simulations which not only confirm but also further enhance our theoretical results. The simulations show that when total input of resource is fixed, smaller input amounts with shorter periods of impulsive delivery produce smaller oscillation amplitudes for both the host and parasitoid populations at the juvenile stage. However, both the densities of adult host and adult parasitoid are not affected by the resource management strategy. Furthermore, we also reconfirm that larger maturation delays, either the host or the parasitoid’s delay, lead to any more individuals staying at the inmature stage of the species, while the adult populations decline dramatically at the same time. On the other hand, larger host maturation delays promote the parasitoid’s population growth at both stages, and the impact of parasitoid maturation delay on the host population is almost the same but not as dramatic. These findings give us a deeper understanding about the host–parasitoid interaction in laboratory environment.

Frequency distribution of lymphatic filariasis microfilariae in human populations: population processes and statistical estimation

Parasitology ◽  
1990 ◽  
Vol 101 (3) ◽  
pp. 417-427 ◽  
Author(s):  
B. T. Grenfell ◽  
P. K. Das ◽  
P. K. Rajagopalan ◽  
D. A. P. Bundy
Keyword(s):  
Lymphatic Filariasis ◽  
Frequency Distribution ◽  
Statistical Estimation ◽  
Negative Binomial ◽  
Wuchereria Bancrofti ◽  
Host Population ◽  
Blood Sampling ◽  
Human Populations ◽  
Poisson Mixtures ◽  
The Impact

SUMMARYThis paper uses simple mathematical models and statistical estimation techniques to analyse the frequency distribution of microfilariae (mf) in blood samples from human populations which are endemic for lymphatic filariasis. The theoretical analysis examines the relationship between microfilarial burdens and the prevalence of adult (macrofilarial) worms in the human host population. The main finding is that a large proportion of observed mf-negatives may be ‘true’ zeros, arising from the absence of macrofilarial infections or unmated adult worms, rather than being attributable to the blood sampling process. The corresponding mf distribution should then follow a Poisson mixture, arising from the sampling of mf positives, with an additional proportion of ‘true’ mf-zeros. This hypothesis is supported by analysis of observed Wuchereria bancrofti mf distributions from Southern India, Japan and Fiji, in which zero-truncated Poisson mixtures fit mf-positive counts more effectively than distributions including the observed zeros. The fits of two Poisson mixtures, the negative binomial and the Sichel distribution, are compared. The Sichel provides a slightly better empirical description of the mf density distribution; reasons for this improvement, and a discussion of the relative merits of the two distributions, are presented. The impact on observed mf distributions of increasing blood sampling volume and extraction efficiency are illustrated via a simple model, and directions for future work are identified.

scholarly journals Bovine tuberculosis breakdown duration in cattle herds: an investigation of herd, host, pathogen and wildlife risk factors

2019 ◽  
Author(s):  
Georgina Milne ◽  
Adrian Allen ◽  
Jordon Graham ◽  
Angela Lahuerta-Marin ◽  
Carl McCormick ◽  
...  
Keyword(s):  
Bovine Tuberculosis ◽  
Negative Binomial ◽  
Disease Risk ◽  
Financial Burden ◽  
Univariate Analysis ◽  
Positive Association ◽  
Herd Size ◽  
Movement Restriction ◽  
Factors Associated ◽  
The Impact

Background. Despite rigorous controls placed on herds which disclose antemortem test positive cattle to bovine tuberculosis, caused by the infection of Mycobacterium bovis, many herds in Northern Ireland (NI) experience prolonged breakdowns. These herds represent a considerable administrative and financial burden to the State and farming community. Methods. A retrospective observational study was conducted to better understand the factors associated with breakdown duration, which was modelled using both negative binomial and ordinal regression approaches. Six explanatory variables were important predictors of breakdown length in both models; herd size, the number of reactors testing positive in the initial SICCT test, the presence of a lesioned animal at routine slaughter (LRS), the count of M. bovis genotypes during the breakdown (MLVA richness), the local herd-level bTB prevalence, and the presence of herds linked via management factors (associated herds). Results. We report that between 2008 and 2014, mean breakdown duration in NI was 226 days (approx. seven months; median; 188 days). In the same period, however, more than 6% of herds in the region remained under movement restriction for more than 420 days (13 months); almost twice as long as the mean. The MLVA richness variable was a particularly important predictor of breakdown duration. We contend that this variable primarily represents a proxy for beef fattening herds, which can operate by purchasing cattle and selling animals straight to slaughter, despite prolonged trading restrictions. For other herd types, the model supports the hypothesis that prolonged breakdowns are a function of both residual infection within the herd, and infection from the environment (e.g. infected wildlife, contiguous herds and/or a contaminated environment). The impact of badger density on breakdown duration was assessed by including data on main sett (burrow) density. Whilst a positive association was observed in the univariate analysis, confounding with other variables means that the contribution of badgers to prolonged breakdowns was not clear from our study. We do not fully reject the hypothesis that badgers are implicated in prolonging bTB breakdowns via spillback infection, but given our results, we posit that increased disease risk from badgers is unlikely to simply be a function of increasing badger density measured using sett metrics.

scholarly journals Bovine tuberculosis breakdown duration in cattle herds: an investigation of herd, host, pathogen and wildlife risk factors

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8319 ◽  
Author(s):  
Georgina Milne ◽  
Adrian Allen ◽  
Jordon Graham ◽  
Angela Lahuerta-Marin ◽  
Carl McCormick ◽  
...  
Keyword(s):  
Bovine Tuberculosis ◽  
Negative Binomial ◽  
Disease Risk ◽  
Financial Burden ◽  
Univariate Analysis ◽  
Positive Association ◽  
Herd Size ◽  
Movement Restriction ◽  
Factors Associated ◽  
The Impact

Background Despite rigorous controls placed on herds which disclose ante-mortem test positive cattle to bovine tuberculosis, caused by the infection of Mycobacterium bovis, many herds in Northern Ireland (NI) experience prolonged breakdowns. These herds represent a considerable administrative and financial burden to the State and farming community. Methods A retrospective observational study was conducted to better understand the factors associated with breakdown duration, which was modelled using both negative binomial and ordinal regression approaches. Results Six explanatory variables were important predictors of breakdown length in both models; herd size, the number of reactors testing positive in the initial SICCT test, the presence of a lesioned animal at routine slaughter (LRS), the count of M. bovis genotypes during the breakdown (MLVA richness), the local herd-level bTB prevalence, and the presence of herds linked via management factors (associated herds). We report that between 2008 and 2014, mean breakdown duration in NI was 226 days (approx. seven months; median: 188 days). In the same period, however, more than 6% of herds in the region remained under movement restriction for more than 420 days (13 months); almost twice as long as the mean. The MLVA richness variable was a particularly important predictor of breakdown duration. We contend that this variable primarily represents a proxy for beef fattening herds, which can operate by purchasing cattle and selling animals straight to slaughter, despite prolonged trading restrictions. For other herd types, the model supports the hypothesis that prolonged breakdowns are a function of both residual infection within the herd, and infection from the environment (e.g. infected wildlife, contiguous herds and/or a contaminated environment). The impact of badger density on breakdown duration was assessed by including data on main sett (burrow) density. Whilst a positive association was observed in the univariate analysis, confounding with other variables means that the contribution of badgers to prolonged breakdowns was not clear from our study. We do not fully reject the hypothesis that badgers are implicated in prolonging bTB breakdowns via spillback infection, but given our results, we posit that increased disease risk from badgers is unlikely to simply be a function of increasing badger density measured using sett metrics.

scholarly journals Mass testing and treatment for malaria followed by weekly fever screening, testing and treatment in Northern Senegal: feasibility, cost and impact

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Ruben O. Conner ◽  
Yakou Dieye ◽  
Michael Hainsworth ◽  
Adama Tall ◽  
Badara Cissé ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Intervention Package ◽  
High Coverage ◽  
Transmission Season ◽  
Test And Treat ◽  
Catchment Areas ◽  
Comparison Groups ◽  
Quasi Experimental ◽  
The Impact

Abstract Background Population-wide interventions using malaria testing and treatment might decrease the reservoir of Plasmodium falciparum infection and accelerate towards elimination. Questions remain about their effectiveness and evidence from different transmission settings is needed. Methods A pilot quasi-experimental study to evaluate a package of population-wide test and treat interventions was conducted in six health facility catchment areas (HFCA) in the districts of Kanel, Linguère, and Ranérou (Senegal). Seven adjacent HFCAs were selected as comparison. Villages within the intervention HFCAs were stratified according to the 2013 incidences of passively detected malaria cases, and those with an incidence ≥ 15 cases/1000/year were targeted for a mass test and treat (MTAT) in September 2014. All households were visited, all consenting individuals were tested with a rapid diagnostic test (RDT), and, if positive, treated with dihydroartemisinin-piperaquine. This was followed by weekly screening, testing and treatment of fever cases (PECADOM++) until the end of the transmission season in January 2015. Villages with lower incidence received only PECADOM++ or case investigation. To evaluate the impact of the interventions over that transmission season, the incidence of passively detected, RDT-confirmed malaria cases was compared between the intervention and comparison groups with a difference-in-difference analysis using negative binomial regression with random effects on HFCA. Results During MTAT, 89% (2225/2503) of households were visited and 86% (18,992/22,170) of individuals were tested, for a combined 77% effective coverage. Among those tested, 291 (1.5%) were RDT positive (range 0–10.8 by village), of whom 82% were < 20 years old and 70% were afebrile. During the PECADOM++ 40,002 visits were conducted to find 2784 individuals reporting fever, with an RDT positivity of 6.5% (170/2612). The combination of interventions resulted in an estimated 38% larger decrease in malaria case incidence in the intervention compared to the comparison group (adjusted incidence risk ratio = 0.62, 95% CI 0.45–0.84, p = 0.002). The cost of the MTAT was $14.3 per person. Conclusions It was operationally feasible to conduct MTAT and PECADOM++ with high coverage, although PECADOM++ was not an efficient strategy to complement MTAT. The modest impact of the intervention package suggests a need for alternative or complementary strategies.

scholarly journals The impact of climate variability and change on cryptosporidiosis and giardiasis rates in New Zealand

2010 ◽  
Vol 8 (3) ◽  
pp. 561-571 ◽  
Author(s):  
Emma Britton ◽  
Simon Hales ◽  
Kamalesh Venugopal ◽  
Michael G Baker
Keyword(s):  
Climate Change ◽  
New Zealand ◽  
Climate Variability ◽  
Water Supply ◽  
Negative Binomial ◽  
Spatial Relationship ◽  
Positive Association ◽  
Domestic Water ◽  
The Impact

Aim: To investigate the spatial relationship between climate variability and cryptosporidiosis and giardiasis notifications in New Zealand between 1997 and 2006. Methods: Negative binomial regression was used to analyse spatial relationships between cryptosporidiosis and giardiasis notifications in New Zealand between 1997 and 2006, and climatological average rainfall and temperature at the Census Area Unit (CAU) level. The quality of domestic water supplies, urban-rural status and deprivation were included as covariates. Main results: Giardiasis: There was a positive association between rainfall and giardiasis and between temperature and giardiasis. Cryptosporidiosis: There was a positive association between rainfall and cryptosporidiosis and a negative association between temperature and cryptosporidiosis. The effect of rainfall was modified by the quality of the domestic water supply. Conclusions: These findings suggest that climate variability affects protozoan disease rates in New Zealand. However, predicting the effect of climate change from this study is difficult, as these results suggest that the projected increases in temperature and rainfall may have opposing effects on cryptosporidiosis rates. Nevertheless, water supply quality appeared to modify the impact of increased rainfall on cryptosporidiosis rates. This finding suggests that improving water supply quality in New Zealand could reduce vulnerability to the impact of climate change on protozoan diseases.

Parasite aggregations in host populations using a reformulated negative binomial model

2004 ◽  
Vol 78 (1) ◽  
pp. 57-61 ◽  
Author(s):  
P. Pal ◽  
J.W. Lewis
Keyword(s):  
Negative Binomial ◽  
Host Population ◽  
Distribution Model ◽  
Cumulative Probability ◽  
Heligmosomoides Polygyrus ◽  
Specific Level ◽  
Parasite Aggregation ◽  
High Degree ◽  
Binomial Function

AbstractThe negative binomial distribution model is reformulated and used to demarcate a host population at a specific level of infection by defining an attribute spanning a range of parasite aggregations. The upper limit of the range specifies the boundary for the classification of the host population and provides a technique to determine the cumulative probability at any level of parasite infection to a high degree of accuracy. This approach also leads to the evaluation of thekparameter, i.e. an inverse measure of dispersion of parasite aggregation, for each fraction of the host population with a discrete level of infection. The basic mathematical premise of the negative binomial function is unaltered in developing this reformulation which was applied to data on the distribution of the trichostrongylid nematodeHeligmosomoides polygyrusin populations of the field mouse,Apodemus sylvaticus.

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