A non-parametric method for the reconstruction of age- and time-dependent incidence from the prevalence data of irreversible diseases with differential mortality.

A method is proposed for reconstructing the time and age dependence of incidence rates from successive age-prevalence cross sections taken from the sentinel surveys of irreversible diseases when there is an important difference in mortality between the infected and susceptible subpopulations. The prevalence information at different time-age points is used to generate a surface; the time-age variations along the life line profiles of this surface and the difference in mortality rates are used to reconstruct the time and age dependence of the incidence rate. Past attempts were based on specified parametric forms for the incidence or on the hypothesis of time-invariant forms for the age-prevalence cross sections. The proposed method makes no such assumptions and is thus capable of coping with rapidly evolving prevalence situations. In the simulations carried out, it is found to be resilient to important random noise components added to a prescribed incidence rate input. The method is also tested on a real data set of successive HIV age-prevalence cross sections from Burundi coupled to differential mortality data on HIV(+) and HIV(-) individuals. The often-made assumption that the incidence rate can be written as the product of a calendar time component and an age component is also examined. In this case, a pooling procedure is proposed to estimate the time and the age profiles of the incidence rate using the reconstructed incidence rates at all time-age points.     

Canine leishmaniasis in Campania: new and old foci

Canine Leishmaniasis (CanL) is endemic in Campania Region (Italy) and is strictly related to Human Visceral Leishmaniasis. Past and present reports of the prevalence in the Region show that exist places were CanL has been known for a century (Vesuvius and Ischia Foci) and other localities where the disease appears to be recent (Caserta and Salerno provinces); moreover, the zoonosis is seen not only in endemic foci (autochthonous), but also in non-endemic areas (imported cases), for example in the Benevento and Avellino provinces. Two zymodemes have been identified in human and canine population and also in sandflies: MON 1 and MON 72. Endemic or stable CanL foci correspond with Vesuvius Area, Ischia island, Maddaloni and neighbouring Commons, other foci in the Salerno province. These foci are associated with optimal ecological condition, abundance of reservoirs and hosts, abundance of phlebotomine vectors, prevalence in canine population around 10-40%, incidence in canine population 5%, risk for human population 0.002%. Instable foci occur at the border of the stable foci: they may be the result of changes in climate with the occasional introduction of infected dogs in the areas; in the foci are registered low presence of phlebotomine vectors, prevalence around 0.5-3%, sporadic human cases. Today, in Campania region CanL undoubtedly has an increased incidence and a wider geographic distribution than before: new cases are now reported in areas that were previously non-endemic. Ecological, demographic and environmental changes, large population movements, urbanization have led to an increased incidence and to importation into suburbs with high densities of people and sand-flies. These changes include "global warming", increased number of stray dogs, dogs and population movements, changes in human population (increased number of immune-depressed and old people). Nowadays, the most important focus of CanL and Human Visceral Leishmaniasis of the Mediterranean area is located in Campania Region: during the year 2000, 143 cases of Human Visceral Leishmaniasis have been recorded in Italy, an half of them (83 cases) in Campania region.     

The use of operational modeling of HIV/AIDS in a systems approach to public health decision making.

Compartmental models of infectious diseases readily represent known biological and epidemiological processes, are easily understood in flow-chart form by administrators, are simple to adjust to new information, and lend themselves to routine statistical analysis such as parameter estimation and model fitting. Technical results are immediately interpretable in epidemiological and public health terms. Deterministic models are easily stochasticized where this is important for practical purposes. With HIV/AIDS, serial data on both HIV prevalence and AIDS morbidity have been available from San Francisco. Assuming the distribution of the incubation period to be biologically stable, statistical analysis is quite feasible in other regions, even those with no reliable HIV data. Transmission rates must be estimated locally. It is also often possible to estimate the effective size of a population subgroup at risk, from population data on AIDS morbidity only. Computer simulation provides estimates of the evolving pattern of both HIV prevalence and AIDS morbidity. Some public health questions can be answered only by appropriately formulated stochastic models.     

A mover-stayer model for longitudinal marker data

Studies of chronic disease often focus on estimating prevalence and incidence in which the presence of active disease is based on dichotomizing a continuous marker variable measured with error. Examples include hypertension, asthma, and depression, where active disease is defined by setting a threshold on a continuous measure of blood pressure, respiratory function, and mood, respectively. This paper proposes a model for inference about prevalence and incidence when active disease is determined by dichotomizing a continuous marker variable in a population-based study. In this formulation, it is postulated that there are three groups of people, those that are not susceptible to the disease, those who are always in the disease state, and those who have the potential to transition between the disease and the disease-free states over time. The model is used to estimate the prevalence and incidence of the disease in the population while accounting for measurement error in the marker. An EM algorithm is used for parameter estimation and the methodology is illustrated on Framingham heart study hypertension data. A simulation study is conducted in order to demonstrate the importance of accounting for measurement error in estimating prevalence and incidence for this example.     

Estimating biomarker-based HIV incidence using prevalence data in high risk groups with missing outcomes

The novel two-step serologic sensitive/less sensitive testing algorithm for detecting recent HIV seroconversion (STARHS) provides a simple and practical method to estimate HIV-1 incidence using cross-sectional HIV seroprevalence data. STARHS has been used increasingly in epidemiologic studies. However, the uncertainty of incidence estimates using this algorithm has not been well described, especially for high risk groups or when missing data is present because a fraction of sensitive enzyme immunoassay (EIA) positive specimens are not tested by the less sensitive EIA. Ad hoc methods used in practice provide incorrect confidence limits and thus may jeopardize statistical inference. In this report, we propose maximum likelihood and Bayesian methods for correctly estimating the uncertainty in incidence estimates obtained using prevalence data with a fraction missing, and extend the methods to regression settings. Using a study of injection drug users participating in a drug detoxification program in New York city as an example, we demonstrated the impact of underestimating the uncertainty in incidence estimates using ad hoc methods. Our methods can be applied to estimate the incidence of other diseases from prevalence data using similar testing algorithms when missing data is present.     

Declining hysterectomy prevalence and the estimated impact on uterine cancer incidence in Scotland

AimThe prevalence of hysterectomy is decreasing worldwide. It is not clear whether changes in the population at risk (women with intact uteruses) have contributed to an increased uterine cancer incidence. This study aims to assess the effect of changing trends in hysterectomy prevalence on uterine cancer incidence in Scotland.MethodsThe population of women aged ≥25 years with intact uteri was estimated using the estimated hysterectomy prevalence in 1995 and the number of procedures performed in Scotland (1996–2015). Age-standardized uterine cancer incidence was estimated using uncorrected (total) or corrected (adjusted for hysterectomy prevalence) populations as denominators and the number of incident cancers as numerators. Annual percentage change in uterine cancer was estimated.ResultsHysterectomy prevalence fell from 13% to 10% between 1996–2000 and 2011–2015, with the most marked decline (from 20% to 6%) in the 50–54-year age group. After correction for hysterectomy prevalence, age-standardized incidence of uterine cancer increased by 20–22%. Annual percentage change in incidence of uterine cancer remained stable through the study period and was 2.2% (95%CI 1.8–2.7) and 2.1% (95%CI 1.7–2.6) for uncorrected and corrected estimates, respectively.ConclusionUterine cancer incidence in Scotland corrected for hysterectomy prevalence is higher than estimates using a total female population as denominator. The annual percentage increase in uterine cancer incidence was stable in both uncorrected and corrected populations despite a declining hysterectomy prevalence. The rise in uterine cancer incidence may thus be driven by other factors, including an ageing population, changing reproductive choices, and obesity.     

A machine learning method for estimating the probability of presence using presence‐background data

Estimating the prevalence or the absolute probability of the presence of a species from presence‐background data has become a controversial topic in species distribution modelling. In this paper, we propose a new method by combining both statistics and machine learning algorithms that helps overcome some of the known existing problems. We have also revisited the popular but highly controversial Lele and Keim (LK) method by evaluating its performance and assessing the RSPF condition it relies on. Simulations show that the LK method with the RSPF assumptions would render fragile estimation/prediction of the desired probabilities. Rather, we propose the local knowledge condition, which relaxes the predetermined population prevalence condition that has so often been used in much of the existing literature. Simulations demonstrate the performance of the new method utilizing the local knowledge assumption to successfully estimate the probability of presence. The local knowledge extends the local certainty or the prototypical presence location assumption, and has significant implications for demonstrating the necessary condition for identifying absolute (rather than relative) probability of presence from presence background without absence data in species distribution modelling.     

Is poliomyelitis a serious problem in developing countries?--lameness in Ghanaian schools.

A postal survey of lameness in schools throughout Ghana showed an estimated prevalence of lameness attributable to poliomyetitis of 5-8 per 1000 school-aged children and an estimated mean annual incidence of paralytic poliomyelitis of 23 per 100 000 population. Official reported incidence rates range from 0-1 to 2-1 per 100 000 population, indicating that at least 90% of cases are not reported. No evidence of epidemics was found to account for these high rates. These suggest that mean annual incidence rates in tropical endemic countries have always been as great, if not greater, than those experienced by temperate countries during epidemic periods in the twentieth century and that the total number of cases of paralytic poliomyelitis occurring in the world each year has been reduced by only 25% since the advent of polio vaccine. Immunisation against poliomyelitis must have a high priority in Ghana and other tropical countries where the disease is endemic.     

A general measure of human population growth regulation

A general measure relating the relative effects of mortality and fertility in damping population growth has been derived from stable population theory. This measure, called the Index of Growth Regulation, can be calculated from a life table and a fertility schedule. It is a single number which integrates the fertility and mortality aspects of a population. It has intuitive meaning, and can be related to social aspects of the population. It can be used to compare any two populations, and for this purpose it has advantages over traditional comparative statistics such as life expectancy, which consider only mortality. By selecting life tables representing general stages of human cultural evolution, it has been shown that hunting-gathering populations were regulated more by mortality than by fertility factors. That is, more growth which could have occurred did not occur due to the incidence of mortality than to the incidence of infecundity. The two forces were of about equal weight before the industrial revolution, and fertility has had a predominant role in population regulation since the beginning of industrialization.     

Estimating incidence from prevalence in generalised HIV epidemics: methods and validation

Background

HIV surveillance of generalised epidemics in Africa primarily relies on prevalence at antenatal clinics, but estimates of incidence in the general population would be more useful. Repeated cross-sectional measures of HIV prevalence are now becoming available for general populations in many countries, and we aim to develop and validate methods that use these data to estimate HIV incidence.

Methods and Findings

Two methods were developed that decompose observed changes in prevalence between two serosurveys into the contributions of new infections and mortality. Method 1 uses cohort mortality rates, and method 2 uses information on survival after infection. The performance of these two methods was assessed using simulated data from a mathematical model and actual data from three community-based cohort studies in Africa. Comparison with simulated data indicated that these methods can accurately estimates incidence rates and changes in incidence in a variety of epidemic conditions. Method 1 is simple to implement but relies on locally appropriate mortality data, whilst method 2 can make use of the same survival distribution in a wide range of scenarios. The estimates from both methods are within the 95% confidence intervals of almost all actual measurements of HIV incidence in adults and young people, and the patterns of incidence over age are correctly captured.

Conclusions

It is possible to estimate incidence from cross-sectional prevalence data with sufficient accuracy to monitor the HIV epidemic. Although these methods will theoretically work in any context, we have able to test them only in southern and eastern Africa, where HIV epidemics are mature and generalised. The choice of method will depend on the local availability of HIV mortality data.     

Seroepidemiology of hepatitis A virus in Japan

A seroepidemiologic study to detect class-specific antibody against hepatitis A virus (HAV) was made with 831 randomly collected sera (415 in 1973 and 416 in 1984) from healthy Japanese. Competitive-inhibition, IgG, IgA, and IgM anti-HAV enzyme-linked immunosorbent assays (ELISA) were used. Both collections showed a low prevalence of IgG anti-HAV in young age groups and it increased rapidly at middle age and plateued at greater than or equal to 94% prevalence in the older age groups. However, two age groups spanning ages 25-34 demonstrated statistically lower IgG anti-HAV age prevalences in 1984 vs 1973 (P less than 0.001), with an average 10-year prevalence shift. These data suggest that there has been no significant level of HAV infection to alter antibody prevalences in Japan from 1973 to 1984. The markedly decreased incidence of HAV infection in Japan has created a presently large and growing population of HAV susceptibles.     

Bayesian evidence synthesis for a transmission dynamic model for HIV among men who have sex with men

Understanding infectious disease dynamics and the effect on prevalence and incidence is crucial for public health policies. Disease incidence and prevalence are typically not observed directly and increasingly are estimated through the synthesis of indirect information from multiple data sources. We demonstrate how an evidence synthesis approach to the estimation of human immunodeficiency virus (HIV) prevalence in England and Wales can be extended to infer the underlying HIV incidence. Diverse time series of data can be used to obtain yearly "snapshots" (with associated uncertainty) of the proportion of the population in 4 compartments: not at risk, susceptible, HIV positive but undiagnosed, and diagnosed HIV positive. A multistate model for the infection and diagnosis processes is then formulated by expressing the changes in these proportions by a system of differential equations. By parameterizing incidence in terms of prevalence and contact rates, HIV transmission is further modeled. Use of additional data or prior information on demographics, risk behavior change and contact parameters allows simultaneous estimation of the transition rates, compartment prevalences, contact rates, and transmission probabilities.     

Determining rate constants for irreversible polymerization where the initial step and propagation steps have different rate constants: Consideration of polyadenylate polymerase

A new relationship is derived between the amount of monomer incorporated and the amount of initiated primer in an irreversible polymerization where the first step, initiation, has a rate constant differing from the elongation rate constants. It is valid for template directed and template independent polymerization. This relationship can be used in kinetic simulation. It suggests a simpler curve fitting technique to attain rate constants from a relatively small data set. Our analysis reveals some limitations of the model of irreversible polymerization; these limitations have not been obvious previously. For example, the initiation rate constant is not attainable from simple monomer incorporation data. Reliable rate constants can be obtained with minimal time course studies.     

Estimating incidence curves of several infections using symptom surveillance data

We introduce a method for estimating incidence curves of several co-circulating infectious pathogens, where each infection has its own probabilities of particular symptom profiles. Our deconvolution method utilizes weekly surveillance data on symptoms from a defined population as well as additional data on symptoms from a sample of virologically confirmed infectious episodes. We illustrate this method by numerical simulations and by using data from a survey conducted on the University of Michigan campus. Last, we describe the data needs to make such estimates accurate.     

The Conselice Study of Brain Ageing

Among the age-related diseases, the development of cognitive impairments, in particular dementia, is the most devastating for the individual and has great social and healthcare costs. Accurate information is needed about the prevalence and incidence of cognitive disorders and the physiology of the ageing brain. In particular, only scant data are available about the relationship between ageing, cognitive status and nutritional factors. In order to address these issues we planned the Conselice Study of Brain Ageing, a longitudinal study of physiologic and pathologic brain ageing. The center involved in the study was the municipality of Conselice, Ravenna province, in the Northern Italian region Emilia-Romagna. A total of 1016 subjects aged 65 and over was enrolled at baseline. Information about cognitive status at 4-years of follow-up was collected for 940 of them. These data have been used to estimate prevalence and incidence of dementia in the elderly Italian population and to investigate the possible role of baseline blood homocysteine as risk factors for dementia.     

Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods

Neonatal invasive disease caused by Group B Streptococcus (GBS) is responsible for much acute mortality and long-term morbidity. To guide development of better prevention strategies, including maternal vaccines that protect neonates against GBS, it is necessary to estimate the burden of this condition globally and in different regions. Here, we present a Bayesian model that estimates country-specific invasive GBS (iGBS) disease incidence in children aged 0 to 6 days. The model combines different types of epidemiological data, each of which has its own limitations: GBS colonization prevalence in pregnant women, risk of iGBS disease in children born to GBS-colonized mothers and direct estimates of iGBS disease incidence where available. In our analysis, we present country-specific maternal GBS colonization prevalence after adjustment for GBS detection assay used in epidemiological studies. We then integrate these results with other epidemiological data and estimate country-level incidence of iGBS disease including in countries with no studies that directly estimate incidence. We are able to simultaneously estimate two key epidemiological quantities: the country-specific incidence of early-onset iGBS disease, and the risk of iGBS disease in babies born to GBS-colonized women. Overall, we believe our method will contribute to a more comprehensive quantification of the global burden of this disease, inform cost-effectiveness assessments of potential maternal GBS vaccines and identify key areas where data are necessary.     

Estimation of the number of individuals founding colonized populations

A method for estimating the number of founding chromosomes in an isolated population is introduced. The method assumes that n/2 diploid individuals are sampled from a population and that alleles are identified at L unlinked loci. The population is assumed to have been founded T generations in the past by individuals carrying c chromosomes drawn randomly from a known source population, which has also been sampled. If c is small and the population grew rapidly after it was founded, accurate estimates of c can be obtained and those estimates are not sensitive to details of the history of population sizes. If c is larger or the population remained small after it was founded, then estimates of c depend on the history of population sizes. We test the performance of our method on simulated data and demonstrate its use on data from a rainbow trout (Oncorhynchus mykiss) population.     

A General HIV Incidence Inference Scheme Based on Likelihood of Individual Level Data and a Population Renewal Equation

We derive a new method to estimate the age specific incidence of an infection with a differential mortality, using individual level infection status data from successive surveys. The method consists of a) an SI-type model to express the incidence rate in terms of the prevalence and its derivatives as well as the difference in mortality rate, and b) a maximum likelihood approach to estimate the prevalence and its derivatives. Estimates can in principle be obtained for any chosen age and time, and no particular assumptions are made about the epidemiological or demographic context. This is in contrast with earlier methods for estimating incidence from prevalence data, which work with aggregated data, and the aggregated effect of demographic and epidemiological rates over the time interval between prevalence surveys. Numerical simulation of HIV epidemics, under the presumption of known excess mortality due to infection, shows improved control of bias and variance, compared to previous methods. Our analysis motivates for a) effort to be applied to obtain accurate estimates of excess mortality rates as a function of age and time among HIV infected individuals and b) use of individual level rather than aggregated data in order to estimate HIV incidence rates at times between two prevalence surveys.