Empirical evaluation of statistical models for counts or rates

We consider methods for selecting the joint specification of the mean and variance functions in statistical models for rates or counts. Based on analyses of diagnosis-specific hospital discharge rates in Michigan, we show that a Poisson model with an extra variance component for the systematic variation is superior to several other probability models with regard to specification of the error structure. Further, the deviance residual appears superior to the Pearson residual. The proper specification of such variation is crucial for many types of analyses, such as identification of outliers and regression analyses designed to explain the systematic component of the variation.     

Predicting county‐level cancer incidence rates and counts in the USA

Many countries, including the USA, publish predicted numbers of cancer incidence and death in current and future years for the whole country. These predictions provide important information on the cancer burden for cancer control planners, policymakers and the general public. Based on evidence from several empirical studies, the joinpoint (segmented‐line linear regression) model (JPM) has been adopted by the American Cancer Society to estimate the number of new cancer cases in the USA and in individual states since 2007. Recently, cancer incidence in smaller geographic regions such as counties, and local policy makers are increasingly interested with Federal Information Processing Standard code regions. The natural extension is to directly apply the JPM to county‐level cancer incidence data. The direct application has several drawbacks and its performance has not been evaluated. To address the concerns, we developed a spatial random‐effects JPM for county‐level cancer incidence data. The proposed model was used to predict both cancer incidence rates and counts at the county level. The standard JPM and the proposed method were compared through a validation study. The proposed method outperformed the standard JPM for almost all cancer sites, especially for moderate or rare cancer sites and for counties with small population sizes. As an application, we predicted county‐level prostate cancer incidence rates and counts for the year 2011 in Connecticut. Published 2013. This article is a US Government work and is in the public domain in the USA.     

Spatial and temporal patterns in final amendments to provisional disease counts.

This article examines temporal and spatial patterns in the relationship between provisional and amended reports for Hepatitis A and Hepatitis B received from each state by the Centers for Disease Control and Prevention through the U.S. National Notifiable Diseases Surveillance System from 1980 to 1992. It demonstrates that, as the 1980s unfolded, the preliminary disease reports became less representative markers of final disease counts. Practitioners at the state and community levels need to be aware of the temporal and spatial instabilities in such provisional data if they are used to provide early warning of contemporary health aberrations.     

Trends in mortality from melanoma in Canada and prediction of future rates

A long term increase in incidence of and mortality due to malignant melanoma has been observed in all well documented white populations. The major identified cause of melanoma is sun exposure. One would expect predictions of future atmospheric ozone depletion to lead to an increase in ultraviolet radiation (UVR) and in the effects of sun exposure. We consider age-period data for Canadian malignant malanoma mortality. We fit a multiplicative exponential/logistic (MEL) model to the data and extrapolate to AD 2010 hence yielding point estimates of future rates. We obtain total mortality forecasts by multiplying rates by population estimates. We present standard errors for forecasts. We forecast that melanoma will be a much larger burden on the health care system in the early years of the next century than it is at present. We obtain an age-cohort model by a simple transformation of the age-period model. Also, we obtain unconditional probabilities of death due to melanoma both for age-period and age-cohort models. We discuss the assumptions underlying the MEL model that suggest possible relationships between UVR and melanoma.     

Measurement and prediction of the disappearance rates from soil of 6-chloropicolinic acid

6-Chloropicolinic acid is the sole detectable metabolite, other than carbon dioxide, arising from decomposition of 2-chloro-6-(trichloromethyl) pyridine in soil. The pyridine compound is a potent inhibitor of nitrification now in use with ammonium fertilizers. The purpose of this study was to evaluate the relative influence of various soil and climatic factors on rates of degradation of 6-chloropicolinic acid in soil.Experiments with a wide range of soil types (23 soils) demonstrate that the most important factor influencing the decomposition rate of 6-chloropicolinic acid is soil temperature. When temperature is not a variable, the quantity of organic matter (0.9 to 6.9% by weight) and pH (4.8 to 8.1) significantly affect the rate of decomposition, but sand, silt, and clay percentages do not. Moisture content was without apparent effect because the range of values investigated was too narrow.A fractional-order rate law (0.7) describes the disappearance rate best.Application of the Arrhenius equation to the data for the decomposition of 6-chloropicolinic acid in soil indicates an activation energy of 6.57 kcal per mole, suggesting that the chemical is biologically rather than chemically degraded.It was not possible to develop a suitably precise equation for prediction of loss rate as affected by the above soil and climatic factors because undefined biological factors in the soils override the effect of measurable properties of soil and climate.     

Measurement and prediction of the disappearance rates from soil of 6-chloropicolinic acid.

6-Chloropicolinic acid is the sole detectable metabolite, other than carbon dioxide, arising from decomposition of 2-chloro-6-(trichloromethyl) pyridine in soil. The pyridine compound is a potent inhibitor of nitrification now in use with ammonium fertilizers. The purpose of this study was to evaluate the relative influence of various soil and climatic factors on rates of degradation of 6-chloropicolinic acid in soil. Experiments with a wide range of soil types (23 soils) demonstrate that the most important factor influencing the decomposition rate of 6-chloropicolinic acid is soil temperature. When temperature is not a variable, the quantity of organic matter (0.9 to 6.9% by weight) and pH (4.8 to 8.1) significantly affect the rate of decomposition, but sand, silt, and clay percentages do not. Moisture content was without apparent effect because the range of values investigated was too narrow. A fractional-order rate law (0.7) describes the disappearance rate best. Application of the Arrhenius equation to the data for the decomposition of 6-chloropicolinic acid in soil indicates an activation energy of 6.57 kcal per mole, suggesting that the chemical is biologically rather than chemically degraded. It was not possible to develop a suitably precise equation for prediction of loss rate as affected by the above soil and climatic factors because undefined biological factors in the soils override the effect of measurable properties of soil and climate.     

Quality counts

The 'weak and ill-defined' standards of care imposed by the Registered Homes Act of 1984 have meant that quality of care in nursing homes is monitored unevenly or not at all, says Yumiko Arai.     

Spatial and temporal variation in biting rates and parasite transmission potentials of onchocerciasis vectors in Ecuador

The influence of spatial and temporal factors on onchocerciasis transmission by Simulium exiguum s.l. and S. quadrivittatum in Ecuador was investigated to help develop sampling protocols for entomological surveillance of ivermectin programmes. Flies were collected in alternate months (November 1995-November 1996) at four sites each in the hyperendemic communities of San Miguel and El Tigre. A fixed-effects analysis of variance was used to explore the influence on vector abundance of locality, site, month and hour. Infectivity rates detected by dissection and PCR assays were compared. Simulium exiguum s.l. predominated at El Tigre (75%) whereas S. quadrivittatum prevailed at San Miguel (62%). Vector abundance was highest on river banks and outside houses. Biting and infection rates peaked from March to July. Hourly activity patterns were bimodal in S. exiguum but unimodal in S. quadrivittatum. Annual transmission potentials (ATP) for both species combined were 385 and 733 third stage larvae/person in San Miguel and El Tigre respectively, with S. exiguum accounting for 80% of the combined ATP at both localities. We recommend protocols that may maximize detection of parasite transmission. Infection rates thus obtained must be linked with vector density estimates to assess meaningfully host exposure as treatment progresses.     

2010-2017年全国其他感染性腹泻空间聚集情况及预测

目的 了解2010-2017年全国其他感染性腹泻发病时空分布,并建立其他感染性腹泻疾病发病的预测模型。 方法 基于2010-2017年中国公共卫生科学数据中心(https://www.phsciencedata.cn/Share)平台报告的其他感染性腹泻数据,进行空间自相关分析并构建自回归移动平均混合(autoregressive integrated moving average, ARIMA)模型。 结果 全局自相关结果可得2014年、2015年、2016年全国其他感染性腹泻发病呈全局空间正相关,局部自相关结果显示中国2010-2014年和2016-2017年全国均出现“高-高”区域。模型测试结果显示季节乘积ARIMA(0, 1, 2) (0, 1, 1)12模型适用于构建模型的预测。ARIMA模型对该病短期预测有较好的效果。 结论 中国其他感染性腹泻发病总体呈上升趋势,发病在空间分布上有聚集性且有明显的季节性,需加强该病区域防控预防工作。     

Repeatability of paired counts

The Bland and Altman technique is widely used to assess the variation between replicates of a method of clinical measurement. It yields the repeatability, i.e. the value within which 95 per cent of repeat measurements lie. The valid use of the technique requires that the variance is constant over the data range. This is not usually the case for counts of items such as CD4 cells or parasites, nor is the log transformation applicable to zero counts. We investigate the properties of generalized differences based on Box-Cox transformations. For an example, in a data set of hookworm eggs counted by the Kato-Katz method, the square root transformation is found to stabilize the variance. We show how to back-transform the repeatability on the square root scale to the repeatability of the counts themselves, as an increasing function of the square mean root egg count, i.e. the square of the average of square roots. As well as being more easily interpretable, the back-transformed results highlight the dependence of the repeatability on the sample volume used.     

Spatial correlations of mapped malaria rates with environmental factors in Belize,Central America

Background  

The purposes of this study were to map overall malaria incidence rates from 1989 through 1999 for villages in Belize; to assess the seasonal distribution of malaria incidence by region; and to correlate malaria incidence rates with vegetation cover and rivers in villages, using geographic information system technology.