A method for estimating possible parasite-related host mortality, illustrated using data from Callitetrarhynchus gracilis (Cestoda: Trypanorhyncha) in lizardfish (Saurida spp.)

Parasitology ◽  
1986 ◽  
Vol 92 (1) ◽  
pp. 227-243 ◽  
Author(s):  
E. L. Adjei ◽  
A. Barnes ◽  
R. J. G. Lester
Keyword(s):  
Frequency Distribution ◽  
Negative Binomial ◽  
Infected Fish ◽  
Similar Distribution ◽  
Frequency Distributions ◽  
Time Of Infection ◽  
Host Mortality ◽  
Probability Of Death ◽  
Males And Females ◽  
Using Data

SUMMARYThe frequency distribution of parasites in hosts commonly follows a negative binomial or similar distribution. Under certain conditions the magnitude of parasite-associated host mortality can be estimated by comparing the tail of the observed distribution to that of the distribution predicted from the first few points of the data. For the technique to work the following assumptions need to be met: mortality in lightly infected fish must be rare; infection and consequent mortality occur only in fish younger than those sampled; and the frequency distribution of the parasite at the time of infection should conform to a known probability distribution. The method was applied to frequency distributions of blastocysts of Callitetra rhynchus gracilis in 898 Saurida tumbil (Bloch) and 5013 S. undosquamis (Richardson). Parasite-associated mortality in S. tumbil was calculated to be at least 11 % in males and 2% in females. For S. undosquamis, estimated mortality was about 5% in males and 3% in females. The numbers of parasites estimated to produce a 0·5 probability of death, the parasitological equivalent of an LD50 were 3·4 and 5·7 for S. tumbil males and females, and 18 and 3 for S. undosquamis males and females respectively.

Frequency distribution of Wuchereria bancrofti microfilariae in human populations and its relationships with age and sex

Parasitology ◽  
1990 ◽  
Vol 101 (3) ◽  
pp. 429-434 ◽  
Author(s):  
P. K. Das ◽  
A. Manoharan ◽  
A. Srividya ◽  
B. T. Grenfell ◽  
D. A. P. Bundy ◽  
...  
Keyword(s):  
Frequency Distribution ◽  
Negative Binomial ◽  
Age Distribution ◽  
Indirect Evidence ◽  
Wuchereria Bancrofti ◽  
Parameter Estimates ◽  
Human Populations ◽  
Sampling Errors ◽  
Frequency Distributions ◽  
Age And Sex

SUMMARYThis paper examines the effects of host age and sex on the frequency distribution of Wuchereria bancrofti infections in the human host. Microfilarial counts from a large data base on the epidemiology of bancroftian filariasis in Pondicherry, South India are analysed. Frequency distributions of microfilarial counts divided by age are successfully described by zero-truncated negative binomial distributions, fitted by maximum likelihood. Parameter estimates from the fits indicate a significant trend of decreasing overdispersion with age in the distributions above age 10; this pattern provides indirect evidence for the operation of density-dependent constraints on microfilarial intensity. The analysis also provides estimates of the proportion of mf-positive individuals who are identified as negative due to sampling errors (around 5% of the total negatives). This allows the construction of corrected mf age–prevalence curves, which indicate that the observed prevalence may underestimate the true figures by between 25% and 100%. The age distribution of mf-negative individuals in the population is discussed in terms of current hypotheses about the interaction between disease and infection.

scholarly journals Epidemic of charcoal burning suicide in Japan

2014 ◽  
Vol 204 (4) ◽  
pp. 274-282 ◽  
Author(s):  
Eiji Yoshioka ◽  
Sharon J. B. Hanley ◽  
Yasuyuki Kawanishi ◽  
Yasuaki Saijo
Keyword(s):  
Negative Binomial ◽  
Age Groups ◽  
Negative Binomial Regression ◽  
Vital Statistics ◽  
Charcoal Burning ◽  
Binomial Regression ◽  
Males And Females ◽  
Burning Method ◽  
Using Data ◽  
The Impact

BackgroundThe charcoal burning suicide epidemics in both Hong Kong and Taiwan have been well documented. However, little is known about the situation in Japan.AimsTo examine the impact of charcoal burning suicide on the overall and other method-specific suicide rates between 1998 and 2007 in Japan.MethodUsing data obtained from the Vital Statistics of Japan, negative binomial regression analyses were performed to investigate the impact of the charcoal burning method.ResultsIn males and females aged 15–24 and 25–44 years, the charcoal burning epidemic led to a substantial increase in overall suicides, without a decrease in other methods. In all other age groups, no such trend was observed.ConclusionsIn young Japanese, the charcoal burning method may have appealed to individuals who might not have chosen other highly or relatively lethal methods, and consequently led to an increase in overall suicides.

Frequency distribution of Brugia malayi microfilariae in human populations

Parasitology ◽  
1991 ◽  
Vol 102 (2) ◽  
pp. 207-212 ◽  
Author(s):  
A. Srividya ◽  
K. Krishnamoorthy ◽  
S. Sabesan ◽  
K. N. Panicker ◽  
B. T. Grenfell ◽  
...  
Keyword(s):  
Frequency Distribution ◽  
Negative Binomial ◽  
Brugia Malayi ◽  
Large Data ◽  
Human Populations ◽  
Infection Prevalence ◽  
Host Age ◽  
Sampling Errors ◽  
Frequency Distributions ◽  
Over Dispersion

SUMMARYThis study examines the effects of host age and sex on the frequency distribution of Brugia malayi infections in the human host. Microfilarial (mf) counts for a large data base on the epidemiology of brugian filariasis in Shertallai, Kerala, South India are analysed. Frequency distributions of microfilarial counts partitioned by age are successfully described by zero-truncated negative binomial distributions, fitted by maximum likelihood. This analysis provides estimates of the proportion of mf-positive individuals who are identified as negative due to sampling errors, allowing the construction of corrected mf age–prevalence curves, which indicate that the observed prevalence may under-estimate the true figures by between 18 and 47%. There is no evidence from these results for a decrease in the degree of over-dispersion of parasite frequency distributions with host age, such as might be produced by the acquired immunity to infection. This departure from the pattern in bancroftian filariasis (where there is evidence of such decreases in over-dispersion; Das et al. 1990) is discussed in terms of the long history of filariasis control (and consequently low infection prevalence) in Shertallai.

scholarly journals Catchability of the southern rock lobster Jasus edwardsii. II. Effects of size

2002 ◽  
Vol 53 (8) ◽  
pp. 1149 ◽  
Author(s):  
P. E. Ziegler ◽  
C. R. Johnson ◽  
S. D. Frusher ◽  
C. Gardner
Keyword(s):  
Frequency Distribution ◽  
Rock Lobster ◽  
Size Frequency Distribution ◽  
Frequency Distributions ◽  
Size Classes ◽  
Size Frequency ◽  
Jasus Edwardsii ◽  
Behavioural Interactions ◽  
Males And Females ◽  
Relative Selectivity

For most of the year, the size-frequency distribution of trap-caught southern rock lobster, Jasus edwardsii, reflected size-specific catchability rather than the size-frequency distribution of the population in a scientific reserve in Tasmania, Australia. The size-frequency distributions of the population on the ground and of lobsters captured in traps were similar only during a few months, typically during moulting and mating. Small males and females were usually under-represented in traps. Catchability generally increased with size, but varied with sex and season. During moulting and mating, size-specific catchability and relative selectivity of larger animals were similar to or lower than for smaller animals. The relative pattern of catchability throughout the year was similar for most size classes within each sex. Negative associations between small and large lobsters in traps were stronger in winter than in summer, indicating strong behavioural interactions. These interactions could explain the lower catchability of smaller lobsters. Relative selectivity estimates using tag–recapture and size-specific catchability data provided generally similar results.

scholarly journals Estimation of the Actual Incidence of Coronavirus Disease (COVID-19) in Emergent Hotspots: The Example of Hokkaido, Japan during February–March 2020

2021 ◽  
Vol 10 (11) ◽  
pp. 2392
Author(s):  
Andrei R. Akhmetzhanov ◽  
Kenji Mizumoto ◽  
Sung-Mok Jung ◽  
Natalie M. Linton ◽  
Ryosuke Omori ◽  
...  
Keyword(s):  
Cumulative Incidence ◽  
Surveillance System ◽  
Negative Binomial ◽  
Actual Number ◽  
Public Health Response ◽  
The Public ◽  
Health Response ◽  
Using Data ◽  
Insight Into ◽  
Actual Incidence

Following the first report of the coronavirus disease 2019 (COVID-19) in Sapporo city, Hokkaido Prefecture, Japan, on 14 February 2020, a surge of cases was observed in Hokkaido during February and March. As of 6 March, 90 cases were diagnosed in Hokkaido. Unfortunately, many infected persons may not have been recognized due to having mild or no symptoms during the initial months of the outbreak. We therefore aimed to predict the actual number of COVID-19 cases in (i) Hokkaido Prefecture and (ii) Sapporo city using data on cases diagnosed outside these areas. Two statistical frameworks involving a balance equation and an extrapolated linear regression model with a negative binomial link were used for deriving both estimates, respectively. The estimated cumulative incidence in Hokkaido as of 27 February was 2,297 cases (95% confidence interval (CI): 382–7091) based on data on travelers outbound from Hokkaido. The cumulative incidence in Sapporo city as of 28 February was estimated at 2233 cases (95% CI: 0–4893) based on the count of confirmed cases within Hokkaido. Both approaches resulted in similar estimates, indicating a higher incidence of infections in Hokkaido than were detected by the surveillance system. This quantification of the gap between detected and estimated cases helped to inform the public health response at the beginning of the pandemic and provided insight into the possible scope of undetected transmission for future assessments.

scholarly journals Identifying Temporal Aggregation Effect on Crash-Frequency Modeling

2021 ◽  
Vol 13 (11) ◽  
pp. 6214
Author(s):  
Bumjoon Bae ◽  
Changju Lee ◽  
Tae-Young Pak ◽  
Sunghoon Lee
Keyword(s):  
Traffic Safety ◽  
Negative Binomial ◽  
Random Effect ◽  
Temporal Correlation ◽  
Negative Binomial Regression ◽  
Spatiotemporal Analysis ◽  
Parameter Estimates ◽  
Crash Frequency ◽  
Crash Frequency Modeling ◽  
Using Data

Aggregation of spatiotemporal data can encounter potential information loss or distort attributes via individual observation, which would influence modeling results and lead to an erroneous inference, named the ecological fallacy. Therefore, deciding spatial and temporal resolution is a fundamental consideration in a spatiotemporal analysis. The modifiable temporal unit problem (MTUP) occurs when using data that is temporally aggregated. While consideration of the spatial dimension has been increasingly studied, the counterpart, a temporal unit, is rarely considered, particularly in the traffic safety modeling field. The purpose of this research is to identify the MTUP effect in crash-frequency modeling using data with various temporal scales. A sensitivity analysis framework is adopted with four negative binomial regression models and four random effect negative binomial models having yearly, quarterly, monthly, and weekly temporal units. As the different temporal unit was applied, the result of the model estimation also changed in terms of the mean and significance of the parameter estimates. Increasing temporal correlation due to using the small temporal unit can be handled with the random effect models.

Using Tolerance-Maps to Generate Frequency Distributions of Clearance and Allocate Tolerances for Pin-Hole Assemblies

2007 ◽  
Vol 7 (4) ◽  
pp. 347-359 ◽  
Author(s):  
Gaurav Ameta ◽  
Joseph K. Davidson ◽  
Jami J. Shah
Keyword(s):  
Mathematical Model ◽  
Statistical Method ◽  
Frequency Distribution ◽  
Probabilistic Representation ◽  
Worst Case ◽  
Frequency Distributions ◽  
One Dimensional ◽  
Material Condition ◽  
Geometric Tolerances ◽  
Case Basis

A new mathematical model for representing the geometric variations of lines is extended to include probabilistic representations of one-dimensional (1D) clearance, which arise from positional variations of the axis of a hole, the size of the hole, and a pin-hole assembly. The model is compatible with the ASME/ ANSI/ISO Standards for geometric tolerances. Central to the new model is a Tolerance-Map (T-Map) (Patent No. 69638242), a hypothetical volume of points that models the 3D variations in location and orientation for a segment of a line (the axis), which can arise from tolerances on size, position, orientation, and form. Here, it is extended to model the increases in yield that occur when maximum material condition (MMC) is specified and when tolerances are assigned statistically rather than on a worst-case basis; the statistical method includes the specification of both size and position tolerances on a feature. The frequency distribution of 1D clearance is decomposed into manufacturing bias, i.e., toward certain regions of a Tolerance-Map, and into a geometric bias that can be computed from the geometry of multidimensional T-Maps. Although the probabilistic representation in this paper is built from geometric bias, and it is presumed that manufacturing bias is uniform, the method is robust enough to include manufacturing bias in the future. Geometric bias alone shows a greater likelihood of small clearances than large clearances between an assembled pin and hole. A comparison is made between the effects of choosing the optional material condition MMC and not choosing it with the tolerances that determine the allowable variations in position.

Bias in Using an Age–Length Key to Estimate Age-Frequency Distributions

1978 ◽  
Vol 35 (2) ◽  
pp. 184-189 ◽  
Author(s):  
S. J. Westrheim ◽  
W. E. Ricker
Keyword(s):  
Frequency Distribution ◽  
Age Distribution ◽  
Length Distribution ◽  
Fish Population ◽  
Systematic Bias ◽  
Parental Age ◽  
Frequency Distributions ◽  
Class Strength ◽  
Key Words Age ◽  
Age Frequency Distribution

Consider two representative samples of fish taken in different years from the same fish population, this being a population in which year-class strength varies. For the "parental" sample the length and age of the fish are determined and are used to construct an "age–length key," the fractions of the fish in each (short) length interval that are of each age. For the "filial" sample only the length is measured, and the parental age–length key is used to compute the corresponding age distribution. Trials show that the age–length key will reproduce the age-frequency distribution of the filial sample without systematic bias only if there is no overlap in length between successive ages. Where there is much overlap, the age–length key will compute from the filial length-frequency distribution approximately the parental age distribution. Additional bias arises if the rate of growth if a year-class is affected by its abundance, or if the survival rate in the population changes. The length of the fish present in any given part of a population's range can vary with environmental factors such as depth of the water; nevertheless, a sample taken in any part of that range can be used to compute age from the length distribution of a sample taken at the same time in any other part of the range, without systematic bias. But this of course is not likely to be true of samples taken from different populations of the species. Key words: age–length key, bias, Pacific ocean perch, Sebastes alutus

Host mortality and variability in epizootics of Schistocephalus solidus infecting the threespine stickleback, Gasterosteus aculeatus

Parasitology ◽  
2010 ◽  
Vol 137 (11) ◽  
pp. 1681-1686 ◽  
Author(s):  
D. C. HEINS ◽  
E. L. BIRDEN ◽  
J. A. BAKER
Keyword(s):  
Gasterosteus Aculeatus ◽  
Infected Fish ◽  
Threespine Stickleback ◽  
Intensity Of Infection ◽  
Host Fish ◽  
Schistocephalus Solidus ◽  
Second Intermediate Host ◽  
Host Mortality ◽  
Abiotic And Biotic Factors ◽  
Host Behaviour

SUMMARYAn analysis of the metrics of Schistocephalus solidus infection of the threespine stickleback, Gasterosteus aculeatus, in Walby Lake, Alaska, showed that an epizootic ended between 1996 and 1998 and another occurred between 1998 and 2003. The end of the first epizootic was associated with a crash in population size of the stickleback, which serves as the second intermediate host. The likely cause of the end of that epizootic is mass mortality of host fish over winter in 1996–1997. The deleterious impact of the parasite on host reproduction and increased host predation associated with parasitic manipulation of host behaviour and morphology to facilitate transmission might also have played a role, along with unknown environmental factors acting on heavily infected fish or fish in poor condition. The second epizootic was linked to relatively high levels of prevalence and mean intensity of infection, but parasite:host mass ratios were quite low at the peak and there were no apparent mass deaths of the host. A number of abiotic and biotic factors are likely to interact to contribute to the occurrence of epizootics in S. solidus, which appear to be unstable and variable. Epizootics appear to depend on particular and, at times, rare sets of circumstances.

Frequency distribution of space groups in soluble and membrane proteins and their complexes

2021 ◽  
Vol 77 (6) ◽  
pp. 187-191
Author(s):  
Rajneesh K. Gaur
Keyword(s):  
Membrane Proteins ◽  
Frequency Distribution ◽  
Data Bank ◽  
Frequency Distributions ◽  
Space Group ◽  
Space Groups ◽  
Group Frequency ◽  
Different Types ◽  
Analytical Assessment ◽  
Three Space

The space-group frequency distributions for two types of proteins and their complexes are explored. Based on the incremental availability of data in the Protein Data Bank, an analytical assessment shows a preferential distribution of three space groups, i.e. P212121 > P1211 > C121, in soluble and membrane proteins as well as in their complexes. In membrane proteins, the order of the three space groups is P212121 > C121 > P1211. The distribution of these space groups also shows the same pattern whether a protein crystallizes with a monomer or an oligomer in the asymmetric unit. The results also indicate that the sizes of the two entities in the structures of soluble proteins crystallized as complexes do not influence the frequency distribution of space groups. In general, it can be concluded that the space-group frequency distribution is homogenous across different types of proteins and their complexes.

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