Nicotinamide nucleotides in the erythrocytes of patients suffering from pellagra

1. The nicotinamide nucleotide concentrations in the erythrocytes of subjects suffering from pellagra (pellagrins) were not lower than those in normal subjects, but the ability of erythrocytes to synthesize these nucleotides in vitro was significantly lower in pellagrins. 2. The oral administration of 10g. of l-leucine daily for 5 days depressed the nicotinamide nucleotide-synthesizing ability of erythrocytes both in normal subjects and in pellagrins. This was not accompanied by changes in the nucleotide concentration in erythrocytes. 3. Quinolinic acid brought about a significant inhibition of the synthesis of nicotinamide nucleotides in vitro. Such inhibition was partially overcome by increasing the concentration of nicotinic acid in the medium.     

Parameter sensitivity of a model of viral epidemics simulated with Monte Carlo techniques. II. Durations and peaks

This is the second of a series of papers concerning sensitivity analyses of stochastic micropopulation models. A model of epidemic spread of viral infection is used in the series to illustrate the principles and performance of the sensitivity analysis system. For these studies the analysis system now known as SENSEN was redesigned; it can be used with any specialization of the SUMMERS simulation shell. Previous applications of SENSEN and its predecessors studied the sensitivity simultaneously to at most six input parameters. The applicability of SENSEN when twelve input parameters are selected is illustrated by sensitivity analyses of epidemic durations. A time-related output, day of the epidemic at which the peak number of cases are present, is also studied.     

Uncertainty in the tail of the variant Creutzfeldt-Jakob disease epidemic in the UK

Despite low case numbers the variant Creutzfeldt-Jakob disease epidemic poses many challenges for public health planning due to remaining uncertainties in disease biology and transmission routes. We develop a stochastic model for variant CJD transmission, taking into account the known transmission routes (food and red-cell transfusion) to assess the remaining uncertainty in the epidemic. We use Bayesian methods to obtain scenarios consistent with current data. Our results show a potentially long but uncertain tail in the epidemic, with a peak annual incidence of around 11 cases, but the 95% credibility interval between 1 and 65 cases. These cases are predicted to be due to past food-borne transmissions occurring in previously mostly unaffected genotypes and to transmissions via blood transfusion in all genotypes. However, we also show that the latter are unlikely to be identifiable as transfusion-associated cases by case-linking. Regardless of the numbers of future cases, even in the absence of any further control measures, we do not find any self-sustaining epidemics.     

Why Was the 2009 Influenza Pandemic in England So Small?

The "Swine flu" pandemic of 2009 caused world-wide infections and deaths. Early efforts to understand its rate of spread were used to predict the probable future number of cases, but by the end of 2009 it was clear that these predictions had substantially overestimated the pandemic's eventual impact. In England, the Health Protection Agency made announcements of the number of cases of disease, which turned out to be surprisingly low for an influenza pandemic. The agency also carried out a serological survey half-way through the English epidemic. In this study, we use a mathematical model to reconcile early estimates of the rate of spread of infection, weekly data on the number of cases in the 2009 epidemic in England and the serological status of the English population at the end of the first pandemic wave. Our results reveal that if there are around 19 infections (i.e., seroconverters) for every reported case then the three data-sets are entirely consistent with each other. We go on to discuss when in the epidemic such a high ratio of seroconverters to cases of disease might have been detected, either through patterns in the case reports or through even earlier serological surveys.     

Statistical theories of functions and the problem of epidemic disease

Several decades ago, Christopher Boorse formulated an influential statistical theory of normative biological functions but it has often been claimed that his theory suffers from insuperable problems such as an inability to handle cases of epidemic and universal diseases. This paper develops a new statistical theory of normative functions that is capable of dealing with the notorious problem of epidemic and universal diseases. The theory is also more detailed than its predecessors and offers other important advantages over them. It is argued here that statistical theories of biological functions should not be so quickly dismissed.     

Mathematical studies on the sterile insect technique for the Chikungunya disease and Aedes albopictus

Chikungunya is an arthropod-borne disease caused by the Asian tiger mosquito, Aedes albopictus. It can be an important burden to public health and a great cause of morbidity and, sometimes, mortality. Understanding if and when disease control measures should be taken is key to curtail its spread. Dumont and Chiroleu (Math Biosc Eng 7(2):315-348, 2010) showed that the use of chemical control tools such as adulticide and larvicide, and mechanical control, which consists of reducing the breeding sites, would have been useful to control the explosive 2006 epidemic in Réunion Island. Despite this, chemical control tools cannot be of long-time use, because they can induce mosquito resistance, and are detrimental to the biodiversity. It is therefore necessary to develop and test new control tools that are more sustainable, with the same efficacy (if possible). Mathematical models of sterile insect technique (SIT) to prevent, reduce, eliminate or stop an epidemic of Chikungunya are formulated and analysed. In particular, we propose a new model that considers pulsed periodic releases, which leads to a hybrid dynamical system. This pulsed SIT model is coupled with the human population at different epidemiological states in order to assess its efficacy. Numerical simulations for the pulsed SIT, using an appropriate numerical scheme are provided. Analytical and numerical results indicate that pulsed SIT with small and frequent releases can be an alternative to chemical control tools, but only if it is used or applied early after the beginning of the epidemic or as a preventive tool.     

Environment, population, and biology: a short history of modern epidemiology

Since its origin in the 19th century, epidemiology has faced an internal tension between an approach oriented toward biology and the study of mechanisms, and an approach oriented toward populations and their interactions with the environment. Initially, this tension took the form of an opposition between microbiology and statistics. We describe the early roots of the quantitative approach to health and disease and several historical examples of the above tension. The search for the causes of pellagra exemplifies our thesis. In Italy, where pellagra was endemic, contrasting opinions coexisted between the hypothesis of contaminated maize, supported by Cesare Lombroso, and the hypothesis of a prevailing role of poverty and poor nutrition. In the United States, Joseph Goldberger found no evidence for the hypothesis of contaminated maize or for a microbiological agent, but recognized the central role of nutrition. The "cure" Goldberger proposed was land reform, but he continued studying the disease from a mechanistic point of view; shortly after his death, niacin deficiency was identified as the cause of pellagra. The tension between mechanistic and population-based studies is still present within epidemiology and is in fact essential for the success of the discipline.     

A markov chain approach to calculate r(0) in stochastic epidemic models

R(0) has been defined as "The expected number of secondary infections originated by a "typical" infective individual when introduced into a population of susceptibles", and it is perhaps the single most important parameter in epidemic models. A general framework to calculate R(0) that can be applied to complicated stochastic epidemic models that may include demography, several strains, latent or carrier-like states, with or without density-dependent parameters is introduced. This framework helps us to understand the concept of a "typical" infective individual used in the deterministic definition of R(0). The method is illustrated with applications to several epidemic models, including some in which it has been found that the disease may persist even if R(0)<1. It is shown that although the probability of extinction is difficult to calculate in these latter cases, it is possible to give general conditions on the parameters under which eventual extinction is certain.     

Epidemiological determinants of the pattern and magnitude of the vCJD epidemic in Great Britain.

Understanding the epidemiology and aetiology of new-variant Creutzfeldt-Jakob (vCJD) disease in humans has become increasingly important given the scientific evidence linking it to bovine spongiform encephalopathy (BSE) in cattle and hence the wide exposure of the population of Great Britain (GB) to potentially infectious tissue. The recent analysis undertaken to determine the risk to the population from dorsal route ganglia illustrated the danger in presenting point estimates rather than ranges of scenarios in the face of uncertainty. We present a mathematical template that relates the past pattern of the BSE epidemic in cattle to the future course of any vCJD epidemic in humans, and use extensive scenario analysis to explore the wide range of possible outcomes given the uncertainty in epidemiological determinants. We demonstrate that the average number of humans infected by one infectious bovine and the incubation period distribution are the two epidemiological factors that have the greatest impact on epidemic size and duration. Using the time-series of the BSE epidemic and the cases seen to date, we show that the minimum length of the incubation period is approximately nine years, and that at least 20% of the cases diagnosed to date were exposed prior to 1986. We also demonstrate that the current age distribution of vCJD cases can only arise if younger people were either exposed to a greater extent, more susceptible to infection, or have shorter incubation periods. Extensive scenario analyses show that given the information currently available, the very high degree of uncertainty in the future size of the epidemic will remain for the next 3-5 years. Furthermore, we demonstrate that this uncertainty is unlikely to be reduced by mass screening for late-stage infection.     

Growth hormone response to thyrotropin releasing hormone in a pellagrin

An abnormal hyperresponse of GH to intravenous injection of TRH in a 66-year-old female pellagra patient with typical 3'D's was reported. Diagnosis of pellagra was mainly based on her clinical course and manifestations, although serum levels of nicotinic acid and serotonin were within the normal range. Serum vitamin A and B2 levels were low. However, these findings did not exclude the diagnosis. The abnormal GH response to TRH observed in this patient was decreased at 2 months and thoroughly disappeared at 10 months after admission. GH response to arginine showed an exaggerated and sustained response on admission, decreased at 2 months and showed an almost normal pattern at 10 months after admission. TSH and prolactin response to TRH were normal throughout the clinical course. LH and FSH response to LH-RH were exaggerated, suggesting post-menopausal hypogonadism. Cortisol response to ACTH showed slightly sustained reactions at both times of the provocation. Oral glucose tolerance test revealed a slight impairment in this patient. These results suggest that pellagra is one of the disorders which exhibit an abnormal hyperresponse of GH to intravenous administration of TRH.     

Host-mediated modification of Sau3AI restriction in Listeria monocytogenes: prevalence in epidemic-associated strains.

Most major food-related outbreaks of listeriosis have been traced to a cluster of genetically related strains of serovar 4b (epidemic clone). In spite of numerous searches, distinct bacteriologic or virulence-related features unique to these strains have eluded identification, although a restriction fragment length polymorphism (RFLP) characteristic of the epidemic clone has previously been described (W. Zheng and S. Kathariou, Appl. Environ. Microbiol. 61:4310-4314, 1995). We found that DNAs from 75 strains which were derived from three separate outbreaks and which had the epidemic clone-specific RFLP were also invariably resistant to digestion by Sau3AI and other restriction endonucleases sensitive to cytosine methylation at 5' GATC 3' sites. This modification of Sau3AI restriction was host mediated, as it did not persist when DNA was cloned and propagated in Escherichia coli, and was uncommon among other Listeria strains. Epidemic-associated strains with this modification were resistant to infection by phage propagated in a serotype 4b strain which was not known to be involved in an epidemic and which lacked the epidemic clone-specific RFLP. Screening for susceptibility to MboI digestion revealed that these epidemic strains lacked methylation of adenines at GATC sites. This type of modification was rare among Listeria strains and was found in only three (of eight screened) strains of serovar 1/2b, possibly representing one clonal lineage.     

Epidemics in nonrandomly mixing populations: a simulation

Two stochastic, discrete-time simulation models for the spread of an epidemic through a population are presented. The models explore the effects of nonrandom mixing within the population and are based on an SIR epidemic model without vital statistics. They consider a population of preschool children, some of whom attend child care facilities. Disease transmission occurs both within the home neighborhood and at the child care facility used, if any. The two models differ in population size used, population density, the proportions of children using different kinds of care, and the functions used for calculating the probability of disease transmission. Results are presented for seven different variables--length of the epidemic in weeks, number of cases, number of cases in each kind of care (two day care centers, private homes, and children staying at home), and the number of private home providers affected by the epidemic. In addition, the distribution of total epidemic size and the progress of an epidemic are estimated from 25 epidemic trials. The effects of the location of homes of initial cases, the type of care used by initial cases, and the density of the population are discussed. Results from the simulation confirmed the importance of type of care on the risk for disease transmission. Results from all runs of the simulation showed that children who attended a day care center were most likely to become infected, children who went to a private home were intermediate, and children who did not use any day care facility were at the lowest risk. The size and length of the epidemics were related to the presence of the disease in day care centers, regardless of the location of the initial case, and the time at which the disease entered the center(s). The simulations also showed that the geographical distribution of the homes of children attending a particular center was a critical feature involved in the production of epidemics. The center with more widely distributed homes of students was less likely to experience a major epidemic than the center with clustering of student's homes within a neighborhood. This indicates that it is not simply attendance at a day care center that is critical for disease spread, but that the nature of the population of children attending a center is also of critical importance in the actual risk for disease spread within the center. These results are discussed with reference to the spread of hepatitis A among day care centers in Albuquerque, New Mexico.     

Contributions to the mathematical theory of epidemics—I

(1) A mathematical investigation has been made of the progress of an epidemic in a homogeneous population. It has been assumed that complete immunity is conferred by a single attack, and that an individual is not infective at the moment at which he receives infection. With these reservations the problem has been investigated in its most general aspects, and the following conclusions have been arrived at. (2) In general a threshold density of population is found to exist, which depends upon the infectivity, recovery and death rates peculiar to the epidemic. No epidemic can occur if the population density is below this threshold value. (3) Small increases of the infectivity rate may lead to large epidemics; also, if the population density slightly exceeds its threshold value the effect of an epidemic will be to reduce the density as far below the threshold value as initially it was above it. (4) An epidemic, in general, comes to an end, before the susceptible population has been exhausted. (5) Similar results are indicated for the case in which transmission is through an intermediate host.     

Pharmacokinetics of ortho-I-hippurate in the blood and central lymph of the rat.

The authors studied ortho-I-hippurate kinetics in the blood and central lymph in two groups of intact rats and three groups of animals with induced pathological states (cirrhosis, uraemia, malabsorption). A differentiated lipid concentration in the central lymph was induced in intact animals by depriving them of food (the unfed group) or allowing them food (the fed group) before the experiment. All the hippurate kinetic parameters, including lymphatic bioavailability (FL), in the fed group were very close to those in the unfed group, which was also used as the control for the groups with induced pathological states. Cirrhosis, uraemia and malabsorption altered the blood and lymphatic kinetic parameters in many cases, but the changes mostly followed a parallel course so that FL was maintained (except in the uraemia group, in which it fell).     

Factors determining the pattern of the variant Creutzfeldt-Jakob disease (vCJD) epidemic in the UK

Following the emergence of a new variant of Creutzfeldt-Jakob disease (vCJD) 6 years ago, and the gradual rise in clinical cases, there has been increased speculation regarding the overall magnitude of this epidemic in Great Britain. In this paper, we explore the epidemiological factors and uncertainties determining the scale of this epidemic in light of the most recent data on reported vCJD mortality. Our results demonstrate that, while the magnitude of the uncertainty has decreased dramatically since 1996, it is still not possible to predict with any degree of accuracy the final magnitude of this epidemic, with the 95% confidence interval for future cases being from 10 to 7000 deaths. However, short-term projections show that it is unlikely that a dramatic increase in case numbers will be observed in the next 2-5 years (95% confidence interval for 2 years: 10-80 cases, for 5 years: 10-200 cases). The results confirm significant age-dependent susceptibility/exposure to infection, with the likelihood profile demonstrating that those aged between 10 and 20 years are at highest risk of infection. We also demonstrate how projections based on onset data may be substantially biased, and explore the sensitivity of results to assumptions concerning the exposure to bovine spongiform encephalopathy (BSE) and the incubation-period distribution.     

Pandemic (H1N1) 2009 Influenza Community Transmission Was Established in One Australian State When the Virus Was First Identified in North America

Background

In mid-June 2009 the State of Victoria in Australia appeared to have the highest notification rate of pandemic (H1N1) 2009 influenza in the world. We hypothesise that this was because community transmission of pandemic influenza was already well established in Victoria at the time testing for the novel virus commenced. In contrast, this was not true for the pandemic in other parts of Australia, including Western Australia (WA).

Methods

We used data from detailed case follow-up of patients with confirmed infection in Victoria and WA to demonstrate the difference in the pandemic curve in two Australian states on opposite sides of the continent. We modelled the pandemic in both states, using a susceptible-infected-removed model with Bayesian inference accounting for imported cases.

Results

Epidemic transmission occurred earlier in Victoria and later in WA. Only 5% of the first 100 Victorian cases were not locally acquired and three of these were brothers in one family. By contrast, 53% of the first 102 cases in WA were associated with importation from Victoria. Using plausible model input data, estimation of the effective reproductive number for the Victorian epidemic required us to invoke an earlier date for commencement of transmission to explain the observed data. This was not required in modelling the epidemic in WA.

Conclusion

Strong circumstantial evidence, supported by modelling, suggests community transmission of pandemic influenza was well established in Victoria, but not in WA, at the time testing for the novel virus commenced in Australia. The virus is likely to have entered Victoria and already become established around the time it was first identified in the US and Mexico.     

Impact of the Infection Period Distribution on the Epidemic Spread in a Metapopulation Model

Epidemic models usually rely on the assumption of exponentially distributed sojourn times in infectious states. This is sometimes an acceptable approximation, but it is generally not realistic and it may influence the epidemic dynamics as it has already been shown in one population. Here, we explore the consequences of choosing constant or gamma-distributed infectious periods in a metapopulation context. For two coupled populations, we show that the probability of generating no secondary infections is the largest for most parameter values if the infectious period follows an exponential distribution, and we identify special cases where, inversely, the infection is more prone to extinction in early phases for constant infection durations. The impact of the infection duration distribution on the epidemic dynamics of many connected populations is studied by simulation and sensitivity analysis, taking into account the potential interactions with other factors. The analysis based on the average nonextinct epidemic trajectories shows that their sensitivity to the assumption on the infectious period distribution mostly depends on , the mean infection duration and the network structure. This study shows that the effect of assuming exponential distribution for infection periods instead of more realistic distributions varies with respect to the output of interest and to other factors. Ultimately it highlights the risk of misleading recommendations based on modelling results when models including exponential infection durations are used for practical purposes.     

Shifting patterns: malaria dynamics and rainfall variability in an African highland

The long-term patterns of malaria in the East African highlands typically involve not only a general upward trend in cases but also a dramatic increase in the size of epidemic outbreaks. The role of climate variability in driving epidemic cycles at interannual time scales remains controversial, in part because it has been seen as conflicting with the alternative explanation of purely endogenous cycles exclusively generated by the nonlinear dynamics of the disease. We analyse a long temporal record of monthly cases from 1970 to 2003 in a highland of western Kenya with both a time-series epidemiological model (time-series susceptible-infected-recovered) and a statistical approach specifically developed for non-stationary patterns. Results show that multiyear cycles of malaria outbreaks appear in the 1980s, concomitant with the timing of a regime shift in the dynamics of cases; the cycles become more pronounced in the 1990s, when the coupling between disease and rainfall is also stronger as the variance of rainfall increased at the frequencies of coupling. Disease dynamics and climate forcing play complementary and interacting roles at different temporal scales. Thus, these mechanisms should not be viewed as alternative and their interaction needs to be integrated in the development of future predictive models.     

Early estimation of the reproduction number in the presence of imported cases: pandemic influenza H1N1-2009 in New Zealand

We analyse data from the early epidemic of H1N1-2009 in New Zealand, and estimate the reproduction number R. We employ a renewal process which accounts for imported cases, illustrate some technical pitfalls, and propose a novel estimation method to address these pitfalls. Explicitly accounting for the infection-age distribution of imported cases and for the delay in transmission dynamics due to international travel, R was estimated to be (95% confidence interval: 107,1.47). Hence we show that a previous study, which did not account for these factors, overestimated R. Our approach also permitted us to examine the infection-age at which secondary transmission occurs as a function of calendar time, demonstrating the downward bias during the beginning of the epidemic. These technical issues may compromise the usefulness of a well-known estimator of R--the inverse of the moment-generating function of the generation time given the intrinsic growth rate. Explicit modelling of the infection-age distribution among imported cases and the examination of the time dependency of the generation time play key roles in avoiding a biased estimate of R, especially when one only has data covering a short time interval during the early growth phase of the epidemic.     

Prevention of Parent to Child Transmission (PPTCT) Program Data in India: An Emerging Data Set for Appraising the HIV Epidemic

Background

Evidence based resource allocation and decentralized planning of an effective HIV/AIDS response requires reliable information on levels and trends of HIV at national and sub-national geographic levels. HIV sentinel surveillance data from antenatal clinics (HSS-ANC) has been an important data source to assess the HIV/AIDS epidemic in India, but has a number of limitations. We assess the value of Prevention of Parent to Child Transmission (PPTCT) programme data to appraise the HIV epidemic in India.

Methods/Findings

HIV data from PPTCT sites were compared to HSS-ANC and general population level surveys at various geographic levels in the states of Karnataka, Maharashtra and Andhra Pradesh. Chi-square tests were used to ascertain statistical significance. PPTCT HIV prevalence was significantly lower than HSS-ANC HIV prevalence (0.92% vs. 1.22% in Andhra Pradesh, 0.65% vs. 0.89% in Karnataka, 0.52% vs. 0.60% in Maharashtra, p<0.001 for all three states). In all three states, HIV prevalence from PPTCT centres that were part of the sentinel surveillance was comparable to HSS-ANC prevalence but significantly higher than PPTCT centres that were not part of the sentinel surveillance. HIV prevalence from PPTCT data was comparable to that from general population surveys. In all three states, significant declines in HIV prevalence between 2007 and 2010 were observed with the PPTCT data set. District level analyses of HIV trends and sub-district level analysis of HIV prevalence were possible using the PPTCT and not the HSS-ANC data sets.

Conclusion

HIV prevalence from PPTCT may be a better proxy for general population prevalence than HSS-ANC. PPTCT data allow for analysis of HIV prevalence and trends at smaller geographic units, which is important for decentralized planning of HIV/AIDS programming. With further improvements to the system, India could replace its HSS-ANC with PPTCT programme data for surveillance.