Workplace violence has been documented in all sectors, but female-dominated sectors such as health and social services are at particular risk. In 2007-2008, IntraHealth International assisted the Rwanda Ministries of Public Service and Labor and Health to study workplace violence in Rwanda's health sector. This article reexamines a set of study findings that directly relate to the influence of gender on workplace violence, synthesizes these findings with other research from Rwanda, and examines the subsequent impact of the study on Rwanda's policy environment.Fifteen out of 30 districts were selected at random. Forty-four facilities at all levels were randomly selected in these districts. From these facilities, 297 health workers were selected at random, of whom 205 were women and 92 were men. Researchers used a utilization-focused approach and administered health worker survey, facility audits, key informant and health facility manager interviews and focus groups to collect data in 2007. After the study was disseminated in 2008, stakeholder recommendations were documented and three versions of the labor law were reviewed to assess study impact.Thirty-nine percent of health workers had experienced some form of workplace violence in year prior to the study. The study identified gender-related patterns of perpetration, victimization and reactions to violence. Negative stereotypes of women, discrimination based on pregnancy, maternity and family responsibilities and the 'glass ceiling' affected female health workers' experiences and career paths and contributed to a context of violence. Gender equality lowered the odds of health workers experiencing violence. Rwandan stakeholders used study results to formulate recommendations to address workplace violence gender discrimination through policy reform and programs.Gender inequality influences workplace violence. Addressing gender discrimination and violence simultaneously should be a priority in workplace violence research, workforce policies, strategies, laws and human resources management training. This will go a long way in making workplaces safer and fairer for the health workforce. This is likely to improve workforce productivity and retention and the enjoyment of human rights at work. Finally, studies that involve stakeholders throughout the research process are likely to improve the utilization of results and policy impact. Workplace violence--which includes physical assault, verbal abuse, sexual or racial harassment, bullying or mobbing--affects occupational health worldwide. In 2002, the International Labour Organization, International Council of Nurses, World Health Organization, and Public Services International (ILO/ICN/WHO/PSI) Joint Programme on Violence in the Health Sector defined workplace violence as "Incidents where staff are abused, threatened or assaulted in circumstances related to their work, including commuting to and from work, involving an explicit or implicit challenge to their safety, well-being or health" . The pubIn 2007-2008, IntraHealth International collaborated with the Rwandan Ministries of Health, Public Service and Labour, Gender and Family Protection, and Justice, as well as the Rwanda Health Workers union and other stakeholders, to conduct a study of workplace violence in the Rwandan health sector . The stuIn this article, the authors analyze a subset of those study data to examine gender patterns of violence perpetration and victimization in conjunction with other data linking gender and workplace violence. Further, the authors examine other gender-related research from Rwanda to illuminate the connections between societal violence against women and workplace violence. Finally, the authors document stakeholders' recommendations for action and examine the effects that the study findings had on the policy environment within Rwanda, in order to offer suggestions that may assist human resources (HR) leaders and managers to improve the working conditions for and the productivity and retention of the health workforce.Incidents of violence in the workplace occur in all sectors, but employees in female-dominated sectors such as health and social services are particularly vulnerable 6]. Expe. Expe6].At the time of the Rwanda study, the researchers had difficulty finding research on workplace violence that linked gender-based violence or gender discrimination to workplace violence . Most works touched only the surface of a deeper relationship between gender and violence in the health workplace . Baines'de facto and de jure discrimination in all spheres of life  assessment in Rwanda, and little was known about the health workers' experience of workplace violence or any form of discrimination, including gender discrimination . Howeveequality [20]21]))de factoIf organizational culture "neither erases nor diminishes national culture" , then itFormative research was conducted in early 2007 and consisted of interviews with policy makers, a focus group with health personnel, and a review of national labor and gender policies to assess interest and the extent to which various forms of violence were recognized in Rwanda. This formative research informed the development of data collection instruments; the identification of avenues of data analysis; and the generation of culturally appropriate descriptions of workplace violence and gender discrimination, including associated behaviors.Data collection for the study took place in July 2007, and combined qualitative and quantitative approaches to determine the prevalence of workplace violence and its forms, victims, and perpetrators; identify contributing factors to workplace violence, including gender-related factors; describe victims' reactions and consequences; and describe any existing workplace violence policy and programs that could be reinforced or extended to address the issue. The study made use of six data collection tools: a health workers survey, facility manager and key informant interviews, patient focus groups and a facility risk assessment inventory . The forms of violence studied were verbal abuse, bullying, physical attack and sexual harassment. Exploration of the influence of gender on workplace violence focused on individual, organizational, facility-specific and societal factors contributing to workplace violence. The health workers survey included open and closed-ended questions covering forms of gender discrimination not measured in previous studies of workplace violence .After the study report results were disseminated, the researchers conducted new analyses of health worker survey data to better understand the perpetrator/victim dyad, documented the recommendations made by the Rwandan study stakeholder institutions and reviewed the content of three versions of the national code regulating labor in Rwanda, to identify any policy impact the study may have had.The health workers survey was carried out in fifteen of Rwanda's 30 administrative districts, which were selected at random. Within each district, three health facilities were then selected at random. The facility sample included referral hospitals, district hospitals, health centers, clinics, and public health units or health posts, each of which were managed either by the government (public) or by non-governmental organizations authorized by the government (accredited facilities) or, in some cases, by the private sector. The health worker sample consisted of those who were in the randomly selected facilities on the day data collectors arrived at the targeted sites. Wherever possible, female and male health workers were selected to reflect the proportion of men and women believed to be in the population of Rwandan health workers . A total of 297 health workers were surveyed; 205 were women and 92 men. Of the total number, 158 were from urban sites and 139 from rural sites. Among the 44 health facilities' directors, 20 were selected at random to be interviewed. When the director was not available, his/her assistant was interviewed. Table The researchers faced some challenges in documenting gender discrimination. First, de facto discrimination may exist, but may not be perceived or admitted if official policy and public rhetoric strongly promote gender equality and nondiscrimination (as they do in Rwanda), or when discrimination--like violence--is normalized. Second, de facto gender discrimination may exist, but may not be appraised because subjects of discrimination may lack direct evidence. An example of this was seen in the case of vertical segregation in top health facility management, where study respondents did not have access to objective data on the extent of male overrepresentation in the highest health management tier. Third, discrimination may be perceived but hard to substantiate because it is not always possible to access administrative records that contain objective, gender-disaggregated data on training and promotion opportunities or salary. Because of this, future researchers should, whenever possible, try to capture manifestations of gender discrimination and violence through both qualitative and quantitative means. This is not meant to discredit self-reports of discrimination experienced by health workers. However, in some cases it might be possible to link perceptions of discrimination to objective measures such as gender disaggregated data on salary, training attendance or promotions, gender composition of top management positions, or analysis of the allocation of work tasks and workloads.P = 0.00) was found which explained 25% of the variation (Pseudo R-sq = 0.25) and which had an adequate fit. The odds ratio was calculated to determine the chances of workplace violence being experienced. When the odds were above one, the variable increased the odds of violence relative to a variable. Below one, the odds declined relative to a variable. Finally, some graphics may include a denominator that is not the same as the sample size of 297, which indicates the number of responses to that question.Qualitative data were analyzed for content and trends. Survey, interview, and facility data were collated by Rwandan consultants in a database using Excel. Generally, quantitative data were analyzed using a basic statistical package for cross-tabulation of the various prevalence types by variables of interest , and conducting chi-square analyses to determine if distributions deviated significantly from the expected . Trends were further analyzed using bivariate correlation analyses. Logistic regression was used to relate the chance of something happening (i.e. workplace violence) to a set of associated factors , allowing the researchers to assess the strength of the association of the various factors with the chance of workplace violence being experienced. Based on exploration of variables which showed trends toward significance, a logistic regression model was created with the variable "experience of violence" as dependent variable with no-prevalence as the reference category and eleven independent variables. A significant overall model (Chi2(33)-99.95,The planned sample size of 450 was not achieved, because the data available for health worker postings were not up to date, and because of health worker unavailability on the day of the survey, resulting in a smaller sample of 297 survey respondents. About 20% of those sampled were either line managers or senior managers (i.e. facility director), with 3% of the total being senior managers. This could potentially impact the results, but the research team nevertheless kept these staff in to have a sample size big enough for statistical analysis. However, since the senior managers comprised so small a percentage, their influence on the trends is relatively small. Because the data were based on a retrospective survey of self-ascribed respondent behavior over the past year, findings should be taken with some caution, as a response bias is likely to be of some influence. To minimize response bias, culturally appropriate tools in the local language were used and data were obtained by experienced and trained data collectors. The process of informed consent was rigorously followed for each respondent and, if needed, referrals were provided to psychological support services.Studies have shown that those in charge of making policy-related decisions rarely use evaluation findings as the basis for those decisions, and this is likely to apply to research findings as well. In light of this, the research team applied principles of utilization-focused evaluation , to incrViolence was a real problem in Rwandan health workplaces and was perceived as such. Approximately 39% of health workers reported experiencing at least one form of workplace violence in the twelve months prior to the study: 27% of respondents had experienced verbal abuse, 16% were bullied, 7% encountered sexual harassment and 4% were physically assaulted. Verbal abuse was the most prevalent form, and physical violence the least prevalent. Sexual harassment was not the most prevalent form but it was the most frequent for those who experienced it. The prevalence of psychological violence  was greater than that of physical assault.Health worker survey data on the relationship of perpetrator to victim by type of perpetrator and type of violence were sufficiently robust to demonstrate perpetrator-victim patterns, especially for verbal abuse and bullying. Survey respondents were asked what type of perpetrator was involved in the last instance of violence experienced. Figure "Please think of the last time you experienced (X form of) violence at work. 1) How many people perpetrated the violence? 2) Was (were) the perpetrator(s): a) male; b) female; or c) both?" Table Respondents of the health workers survey were also asked the following multiple choice question for each type of violence (noting that a respondent possibly could choose multiple types of violence): Tables "Please think of the last time (instance) you were verbally abused at work," respondents said that they had been verbally abused by a man in 22% of the instances and by a woman in 55% of the instances. Respondents reported that that they had been verbally abused by both men and women in 23% of the instances. Both male and female health workers were more like to be verbally abused by women, at 58% and 54% respectively, with the exception that female victims were more likely to be abused by men and women together. Slightly more than two thirds (68%) of the victims were female health workers, and slightly under one third (32%) were male health workers, which mirror their proportions in the stratified sample.In response to the survey question, "Please think of the last time you were bullied at work," health workers reported that they had been bullied by a man in 55% of the instances and by a woman in 30% of the instances, with the remainder bullied by both. A sizeable majority of male health workers reported they had been bullied by a man (69%) and slightly less than one fifth (19%) had been bullied by a woman at the last instance of bullying. In somewhat less than half (48%) of the last instances of bullying, female health workers reported that the bully was a man, and slightly more than a third (35%) reported the bully had been a woman. Female health workers also reported they had been bullied by both men and women in 16% of the last instances of bullying. Two thirds (66%) of the victims were female health workers and one third (34%) of the victims were male health workers at the last instance of bullying. In terms of a pattern of bullying, we see that men perpetrated bullying in most instances and that the bullying was experienced by men and women according to their proportion in the study sample.In response to the survey question, "Please think of the last time you were sexually harassed at work," health workers reported that they had been sexually harassed by a man in 65% of the instances, by a woman in 20% of the instances, and by both in 15% of the instances. Of the health workers who reported being sexually harassed, one quarter (25%) were men and three quarters (75%) were women, which does not mirror the proportions in the sample. This means that female health workers in this sample were disproportionately victims of sexual harassment. There was a strong pattern for the perpetrator to be the opposite sex of the victim.In response to the survey question, "Please think of the last time you were physically assaulted/attacked at work," we see  that health workers reported that they had been physically attacked by a man in 55% of the last instances, and by a woman in 36% of the instances. Male health workers were more likely to be physically attacked by a man than otherwise; while female health workers were almost equally likely to be physically attacked by either a man or a woman, though slightly more by a man. At the last instance of physical attack, close to two thirds (64%) of the victims were female health workers, and slightly more than one third (36%) of the victims were male health workers, in keeping with the sample proportions.In response to the survey question, not reflect their proportions in the stratified sample, making sexual harassment the form of violence of which female health workers were disproportionately the victims. Female health workers were also more likely to be verbally abused by both women and men. In the pattern of bullying, male health workers were much more likely to be victimized by men. With respect to physical attack, female health workers were more likely to be attacked by a woman or a man, whereas male health workers were more likely to be attacked by men .In this study, gender appeared to be implicated in patterns of perpetration and victimization. Taken together, the Tables "Have you ever left, or considered leaving the health care sector, or this job, due to your experience of (x form of) violence?" most respondents reported that they either did nothing or only considered leaving their  job. Only 4% of male workers reported that they had ever actually quit a job as a result of verbal abuse. Of female workers, 10% and 7% reported that they had ever actually left a job because of bullying and sexual harassment, respectively. These findings suggest that workplace violence is an occurrence that most health workers may feel they can or must live with, almost as a normal part of the job, but that the experiences of bullying and sexual harassment are more likely to result in a female health worker leaving a job.Table The health worker survey data also showed that health workers' disclosure of incidents varied with the type of violence. In most cases--especially those of verbal abuse, bullying, and physical violence--subjects disclosed the incident to colleagues, friends and family. However, in 40% of sexual harassment cases, the victim did not disclose the occurrence to anyone. This was not surprising given the norms of silence around sexual violence in Rwanda. Fewer than 20% of victims of most forms of violence reported the incident to their supervisor. This low overall reportage rate is also not surprising, given that hierarchical superiors (i.e. managers orsupervisors) were reportedly involved in the perpetration of all types of violence  respondents agreed that women did not encounter the same problems as men at work, and 41% agreed that women were more exposed to violence. Sixty-eight per cent of respondents pointed to pregnancy, childbirth, and family and child care responsibilities as factors that prevented women from fully participating at work. Qualitative data from the health workers' survey also suggested that female workers perceived their career progress to have been adversely affected by the unique problems faced by women at work. Some female workers reported that performance evaluations or opportunities for promotion had been influenced by their maternity status; others reported that they had been demoted after pregnancy without cause, or were not hired for a position because of presumed future pregnancy. One respondent noted that "When I had not yet delivered, I was deputy director; after delivery, I was demoted for no reason but I think it was because of my pregnancy."did not appear in the top management jobs at the same rates as men. Even though men made up only about 31% of the sample, they constituted 60% of directors in the sample facilities. These findings suggested that vertical segregation (a form of discrimination) may exist but is not necessarily perceived. However, about one out of four service providers agreed that task assignments for male and female workers occupying the same job differed either in types or volume, suggesting some  gender segregation of tasks that was observable to respondents. As a female study participant noted, "Some people seem to think that certain activities are reserved only for men."The study revealed vertical segregation of the facility director's job by sex (i.e. the 'glass ceiling'). Survey data were analyzed with attention to the number of men and women who occupied the top management (facility director) jobs. While only 16% of health workers in the survey sample believed that women did not have the same chance as men of being hired for jobs for which they are qualified, women actually Sexual harassment, problems at work related to pregnancy and family responsibilities, and occupational segregation co-occurred with negative stereotypes about female health workers, such as an unwillingness to speak up, weakness, indecisiveness and incompetence. One survey respondent observed that women at work "just don't know how to make decisions in a sure and certain way." Another noted that women "are not even capable of pulling out a tooth." These negative stereotypes may be the foundation on which violence (as well as other forms of workplace discrimination) rest. Indeed, according to a key informant, beliefs about Rwandan women in the health workplace rationalize violence: "There is a tendency to say that women are weak in the broadest sense... and, in some cases, the violence that women are subjected to stems from this situation."In this section, we consider the relationship between gender equality in the workplace as one of several variables influencing health workers' experience of violence. The study considered several types of factors as possible contributors to workplace violence: individual factors ; general factors ; facility security; and behavioral factors .six times lower (at 0.2), compared to a setting where there is no equal chance. Further, when men and women receive equal treatment at work, the odds of workplace violence were about five times lower (at 0.2), compared to a setting in which there is no equal treatment. The culture of respect variables are of lesser importance compared to the gender equality variables, though respect between supervisors and staff also especially lowers workplace violence. The gender equality variables are thus considered as the more influential behavioral contributor to reduced workplace violence.Table Figure Sixty per cent of respondents who perceived unequal treatment also indicated that they had experienced some form of workplace violence, compared to 36% of those who perceived equal treatment (Pearson chi2(1) = 9.388, P = 0.002).Further, Figure The participatory, capacity-building approach oriented to relevance of results for stakeholders appeared to increase use of the study results and the impact of the study. Table The study appears to have had impact on the national policy environment in particular, having contributed to the revision of the national Law Regulating Labour in Rwanda and to plans to revise the national GBV policy. First, analysis of Rwanda's three labor laws between 2001, 2007 and 2009 showed an evolution in language, wherein no mention is made of violence in 2001 and 2007, but in the 2009 version , there appears in the national labor law a definition of GBV, and the following Articles :"Section 3: Protection of workers against violence or harassmentArticle 9: Prohibition of gender-based violenceArticle 10: Resignation in case of violenceArticle 11: Prohibition of punishment [for reporting violence]Section 4: Prohibition of discrimination in work matters."The study report, which was subsequently disseminated in other stakeholder meeting venues  was also one of three to be included as a resource for the Ministry of Gender and Family Promotion's revision of the 2010 GBV policy .The study shed light on the types, reactions and contributing factors to, and consequences of, workplace violence. Workplace violence is a real phenomenon within the health sector in Rwanda with individual, organizational, and societal impacts experienced by 39% of the health workers sampled. Male and female staff experienced violence, and mostly did nothing or only thought of leaving the job after the experience, even though the experience of violence was personally traumatic, interpersonally disruptive and organizationally depleting in terms of self-reports of absenteeism and lower productivity.vis a vis violence against women, and the finding about nondisclosure of sexual harassment, it is probable that the prevalence of sexual harassment in Rwandan workplaces is a low estimate. It should be noted, nevertheless, that female workers appeared more likely to leave a job because of bullying and sexual harassment experienced at work, a finding that should be of interest to human resource managers who want to retain female health workers.The study identified ways gender appears to influence workplace violence. The first was in patterns of violence perpetration and victimization. Sexual harassment was a particular problem for female health workers. In light of results from studies on violence against women in Rwanda described earlier, a culture of silence and resignation The second way gender appears to influence violence in health workplaces is in the forms of discrimination faced by female health workers. Sexual harassment co-occurred with problems related to managing pregnancy, motherhood and work, and negative stereotyping of women at work, the latter perhaps rationalizing violence against women in Rwanda's health workplaces. The findings on the over-representation of men in top management jobs and gender-based task assignment point to occupational segregation, a ubiquitous form of gender discrimination that typically results from multiple and accumulating discriminations during childhood, schooling, and entry into a career. The fact that female health workers appear to have experienced more than one type of discrimination and bias suggests a systemic substratum of gender discrimination in the health workplace that also deserves serious attention from HR policy makers and managers, because discriminatory working conditions, along with the experience of violence, can weaken female health workers' ties to the workforce. The finding that male perpetrators are overwhelmingly implicated in bullying male health workers may qualify as a form of gender-based violence worthy of further study. The role of the manager/supervisor in bullying also suggests a need to address the use and abuse of power in HR manager training.Most striking was the finding that gender equality lowers the odds of experiencing violence at work. Put another way, this means that gender inequality at work  increases the odds of violence.The study results suggest that violence against female health workers in Rwandan health workplaces may come about from a "category bias"  in whichFinally, the gender-sensitive, multisectoral recommendations made by the stakeholder institutions and recent changes in Rwanda's labor law to address workplace violence are promising steps towards a goal of making the health sector safer and more gender-equitable for its workforce. It is hoped that the elimination of sexual harassment and other forms of gender discrimination will figure in Rwanda's new (2010) draft of the national GBV policy.Gender discrimination and inequality contribute to violence against women in the health sector. Because the key factors contributing to the emergence of violence in Rwandan health workplaces were institutional and behavioral rather than individual, it is likely that improved HR policy--and management practices that enact and enforce improved policy--could decrease some of the risks for violence. First, workplace violence research and workforce assessments should routinely measure the extent of systemic gender discrimination at work. Second, eliminating gender inequality, bias, and specific forms of discrimination should be a special concern in the development of both HR and workplace violence policies and programs, including reporting systems. HR policies should protect women against violence as well as against losing seniority, promotion prospects, or a job as a result of pregnancy or caring for children and family members. Countries that are signatories to international consensus documents on gender equality, such as the International Labour Organization's (ILO's) four gender equality labor standards, already have a policy context for policy and legal reform  . SectoraGBV: Gender-Based Violence; HR: Human Resources; ILO: International Labour Organization; ICN: International Council for Nurses; MOH: Ministry of Health; PSI: Public Services International; PMTCT: Prevention of Mother to Child Transmission; WHO: World Health Organization.The authors declare that they have no competing interests.CN conducted the formative research, conceptualized the study and designed, oversaw or gave input to all aspects of methodology, data analysis, interpretation, dissemination, report writing and French to English translation. JK reviewed instruments, results and reports, oversaw data collection and coordinated dissemination. GN gave input into formative research, study design, gave policy guidance, and reviewed results and the report. DdV reviewed the tools, developed the data analysis and sampling plans, analyzed data, and reviewed drafts of the study report. All authors reviewed and approved the final manuscript.


The primary objective of this study was to identify the existence of chronic disease multimorbidity patterns in the primary care population, describing their clinical components and analysing how these patterns change and evolve over time both in women and men. The secondary objective of this study was to generate evidence regarding the pathophysiological processes underlying multimorbidity and to understand the interactions and synergies among the various diseases.This observational, retrospective, multicentre study utilised information from the electronic medical records of 19 primary care centres from 2008. To identify multimorbidity patterns, an exploratory factor analysis was carried out based on the tetra-choric correlations between the diagnostic information of 275,682 patients who were over 14 years of age. The analysis was stratified by age group and sex.Multimorbidity was found in all age groups, and its prevalence ranged from 13% in the 15 to 44 year age group to 67% in those 65 years of age or older. Goodness-of-fit indicators revealed sample values between 0.50 and 0.71. We identified five patterns of multimorbidity: cardio-metabolic, psychiatric-substance abuse, mechanical-obesity-thyroidal, psychogeriatric and depressive. Some of these patterns were found to evolve with age, and there were differences between men and women.Non-random associations between chronic diseases result in clinically consistent multimorbidity patterns affecting a significant proportion of the population. Underlying pathophysiological phenomena were observed upon which action can be taken both from a clinical, individual-level perspective and from a public health or population-level perspective. The simultaneous occurrence of various health problems in a given individual, which is defined as multimorbidity, has become the norm rather than the exception Understanding the types of multimorbidity patterns that appear in the elderly, especially the chronic diseases that comprise these patterns, demands an analysis of what happens in the earlier stages of life, how those patterns are shaped from a young age, in what way these diseases are aggregated, which diseases are associated with each other and which are not, as well as the pathophysiological mechanisms that may explain these associations. An improved global understanding of the disease process and the interactions present in an affected individual, rather than the study of individual diseases, is essential so that health systems can design appropriate and timely strategies for raising awareness and improving preventative and clinical approaches to multimorbidity, which currently is a health problem in and of itself Multimorbidity has extraordinary importance not only for the general population but also for healthcare systems. It has been shown to be associated with increased mortality Despite these results, there are very few studies that have analysed multimorbidity in depth; for example, it is unknown to what degree multimorbidity is caused by chance, how multimorbidity patterns differ between age and sex groups, what the possible existence of index diseases is that would in turn give rise to new symptoms and diseases or what the roles of iatrogenic issues are in this phenomenon. Some of these aspects need to be addressed promptly.There are three main methodological reasons for this lack of evidence:First, there is uncertainty among the scientific community regarding the application of statistical methods for the exploration of simultaneously occurring health problems Moreover, progress towards understanding the causes of multimorbidity requires a standardised conceptualisation of the various clinical entities that compose it, as the number and type of diseases together with the various ways of grouping them can significantly affect estimates of the prevalence of multimorbidity and the strength of the identified associations Finally, the performance of large-scale population studies focused on this and other public health problems requires sources of information of proven quality that are accessible to the entire scientific community. In this regard, it is important to highlight the enormous potential of clinical-administrative databases, which are available as a result of the computerisation of medical records in both primary and specialised care. Compared with studies that have been based on survey results, these databases provide access to diagnostic information at the individual and population levels.With respect to these three aspects, this work was based on a statistical methodology that allowed for the identification of statistically relevant patterns of multimorbidity. It applied a previously validated categorisation system for chronic diseases and used diagnostic information from primary care electronic medical records.The primary objective of this study was to identify the existence of chronic disease multimorbidity patterns in the primary care population, describing their clinical components and analysing how these patterns change and evolve over time both in women and men. The secondary objective of this study was to generate evidence regarding the pathophysiological processes underlying multimorbidity and to understand the interactions and synergies among the various diseases.The hypothesis was that there would be patterns of multimorbidity partially expected, predictable and explainable that evolve along patients' life. Such patterns would be composed of risk factors in the early stages of life, of organ disorders in the middle ages, and of disease-related complications in the later years of life. Healthcare systems should consider the resulting evidence when organising and planning their service offerings. Moreover, this study pretends to generate new hypotheses related to unknown causal mechanisms underlying multimorbidity such as iatrogenic effects.This multicentre, retrospective, observational study was performed in primary care centres of the Spanish National Health System. From 1986 on, Spain has a tax-based health system with universal coverage for the entire population. The primary care model is based on multidisciplinary teams consisting of family physicians and nurses. The former coordinate prevention, health promotion, treatment, and community care and they also act as gatekeepers to the healthcare system and therefore to more specialized care. Each team has a geographically delimited population assigned to it and all types of patients and health problems, except for medical emergencies, are initially attended in primary care centres.The selection of centres to participate in this study was conducted based on the following quality inclusion criteria: (a) centres with computerised records for all appointments and with more than two years of experience using this system by all physicians and nurses, (b) those with a percentage of uncoded episodes less than 20%, (c) those with a percentage of notes  listed in uncoded episodes less than 15%, (d) those with a percentage of prescriptions linked to uncoded episodes less than 10%, (e) those with an average number of diagnoses higher than 3.5, and (f) those with a percentage of patients with no diagnostic information less than 10%.After selecting the centres, all patients over the age of 14 who were seen at least once during 2008 by their family doctor were included in the study. The study population was composed of 275,682 individuals belonging to 19 urban health centres . For each of the patients included in the study, demographic and diagnostic variables were extracted from electronic medical records, including the age of the patient as of December 31, 2008, the sex of the patient, and the chronic diagnoses coded according to the International Classification of Primary Care (ICPC) To facilitate the management of the diagnostic information, the episodes were grouped according to the Expanded Diagnostic Clusters (EDC) of the ACG® system. To use this system, a conversion from the ICPC to the International Classification of Diseases (ICD-9-CM) The selection of which chronic diseases to study was based on the recent study by Salisbury et al. This study was favourably evaluated by the Clinical Research Ethics Committee of Aragon (CEICA). Written consent by patients was not needed since the study does not involve interventions on individuals, the use of human biological samples, or the analysis of personally identifiable data. Instead, the present work is based on the statistical analysis of anonymous data contained in previously existing databases which were obtained with prior permission from the corresponding entity.A descriptive analysis of the population was performed by calculating the frequencies of demographic variables. To facilitate the analysis of age, three age ranges were created: 15–44, 45–64 and 65 and over. The remaining analyses were performed separately for each age and sex group. To provide an initial description of the prevalence of multimorbidity, the frequency of EDCs per patient for each group of age and sex was calculated.To determine the associations between diseases that exhibited multimorbidity patterns, an exploratory factor analysis was applied. The aim of this method was to identify sets of variables with a common underlying causal factor. This technique was chosen because, in addition to identifying associations among groups of variables, it allowed for variables to be included in the various patterns.To increase the epidemiological interest of the study, only those EDCs with a prevalence equal to or greater than 1% in each group were included . These EThe extraction of the disease factors was performed using the principal factor method, and it was assumed that the extracted factors did not explain the total variance of the analysed EDCs. To determine the number of factors to extract, a scree plot was utilised in which the eigenvalues of the correlation matrix were represented in descending order. The number of factors extracted corresponds to the sequence number of the eigenvalue that produces the inflection point of the curve The adequacy of the sample used to perform the factor analysis was analysed by measuring the Kaiser-Meyer-Olkin (KMO) for each age and sex group. This parameter takes values between 0 and 1, which are closer to 1 with a greater goodness of fit. In addition, as a measure of model goodness-of-fit, the proportion of cumulative variance was obtained, which describes the variability of the diagnostic data explained by the patterns.For determining which EDCs formed each multimorbidity pattern, those with scores equal to or greater than 0.25 for each factor were selected.Given that multimorbidity is defined as the simultaneous presence of two or more chronic diseases STATA 11.0 software was used to conduct the statistical analysis, and Excel 2007 was used to prepare the graphs.Clinical relevance was studied in three phases. First, two qualified primary care physicians with research and clinical experience independently reviewed the clinical plausibility of disease interactions. Next, a joint analysis of both independent reports was performed by a third physician specialized in public health and experienced in health services research, identifying agreements and disagreements between both family physicians. Last, results were resubmitted to the primary care professionals and discussed in a final consensus meeting. The main arguments and conclusions were also contrasted with a literature review by other members of the research team.The study population consisted of 275,682 patients over the age of 14, and 56.6% of this population was female. Multimorbidity existed in all of the studied groups . An incrThis age and sex group had a KMO sampling adequacy index of 0.66 and a cumulative variance percentage of 26.87% . The scrFor this age and sex group, a KMO value of 0.50 was obtained with a cumulative variance percentage of 14.80% . The scrFor this age and sex group, a KMO value of 0.57 was obtained with a cumulative variance percentage of 22.81% . AlthougThe sampling adequacy of this group had a KMO value of 0.71 with a cumulative variance percentage of 24.72% . The infThe sampling adequacy of this group had a KMO value of 0.68 with a cumulative variance percentage of 23.70% . The scrThe sampling adequacy of this group had a KMO value of 0.68 with a cumulative variance percentage of 24.68% . The scrMost of the studied diseases were present in one single pattern, and only 6 of the 37 diseases that comprised the 5 patterns were associated with more than one pattern; these included lipid metabolism disorders (in men), obesity (in men), congestive heart failure (in women and men), osteoporosis (in men), cardiac arrhythmia (in women) and iron deficiency (in men).This study revealed five specific clinically consistent patterns of multimorbidity in the adult population: cardio-metabolic, psychiatric-substance abuse, mechanical-obesity-thyroidal, psychogeriatric and depressive. Two of them were found to evolve throughout life and differed in their presentation for men and women , three of them affected both sexes , and two of them were present exclusively in men or women  .Those two patterns suggesting an evolution throughout life were composed mainly of risk factors in the youngest age group, of organ disorders in the middle-aged group, and of various disease-related complications in the eldest group.Although there are many examples in the literature of the association between the specific diseases that comprise these patterns, there have been very few population-wide published studies on multimorbidity including the non-elderly population.This multimorbidity pattern was present in both sexes and for all of the age ranges analysed. Although it was especially prevalent among individuals 65 years of age or older , the high prevalence of this pattern in the middle-aged groups should be noted .Its development in men and women was consistent with the disease pathophysiology. In young patients, it was manifested as diabetes, hypertension, obesity and dyslipidaemia In men, this pattern presented at a young age and with a possible common pathophysiological basis of insulin resistance, obesity and their associated inflammatory processes, and negative lifestyles . During middle age, ischemic heart disease, atherosclerosis, myocardial infarction, arrhythmias, dyslipidaemia (with a factor score very close to the established cut-off point), substance abuse, COPD and chronic liver disease were also observed within this pattern. Although this study did not have access to specific information regarding tobacco smoking, it is likely that its prevalence was high in those cases where the abuse of other substances was also high (this information was available). The alcohol-tobacco association could have been the probable cause of the diseases observed, such as chronic liver disease and other related associations. In addition, there are possible underlying iatrogenic causes due to the use of drugs such as statins and fibrates, which can cause the elevation of transaminases at medium and high dosages The presence and the evolution of this cardio-metabolic pattern revealed differences between women and men. In women, although hypertension, obesity and dyslipidaemia were present at a young age, diabetes did not appear until the age range 45–64. Moreover, in this second age group, the expected cardiac complications were not observed, contrary to what happened in men of the same age. Oestrogenic protection and reduced smoking have been previously reported as the primary reasons for reduced cardiac complications in women This multimorbidity pattern appeared only in young men and was found to affect 2% of the individuals studied (n = 837). This pattern consisted of psychopathological processes, such as psychosis and neurosis, which are both likely related to the toxic substance abuse that is also present within this pattern and that commonly affects men at this stage of life In men, this was a complex pattern that could also be denominated mechanical-obesity-thyroidal. It affected 5% of middle-aged individuals and was found to decrease to 2% among individuals aged 65 and over. For men aged 45–64, it is likely that obesity acted as an index disease that favoured the emergence of mechanical disorders due to excess body weight, such as arthropathy, cervical and low back pain, varicose veins of lower extremities, and gastro-oesophageal reflux In women, the mechanical pattern was manifest somewhat differently than in men. It appeared early in life and it was never associated with obesity but rather with thyroid problems, likely in the form of hypothyroidism This multimorbidity pattern appeared in individuals 65 years of age and older and was the second-most prevalent pattern after cardio-metabolic. It was more common in women (17%) than men (14%) and was manifest in the form of dementia, behavioural problems, Parkinson's disease, osteoporosis, chronic skin ulcers and iron deficiency. Heart failure and stroke showed factor scores very close to the established cut-off-point and are among the leading causes of dementia The presence of dementia and Parkinson's disease together with age-related osteoporosis can lead to falls, fractures, the immobility of the patients and the appearance of skin ulcers caused by bed rest among these patients In women, this pattern was slightly different than in men: dementia, cerebrovascular disease and chronic skin ulcers were present. In addition, heart failure, iron deficiencies and cardiac arrhythmia  were present in this pattern, and these were clearly associated with and were the cause of cerebrovascular disease This multimorbidity pattern consisted of only two conditions: depression and behavioural disorders (mainly insomnia). These were strongly associated with one another and were present only in women aged 45–64 and 65 years and over. This was the least prevalent of the five patterns described, as the frequency was less than 0.2% in both age groups. The association between these two clinical conditions has been widely described The two main aspects that influence result-stability are the nature and number of individuals and diseases that are included in the analysis Regarding the statistical methodology used, the exploratory factor analysis applied in this study is the preferred method when the objective is to explore statistically significant stable disease clusters It is noteworthy that this study met most of these standards. The decision to reduce the minimum factor score to 0.25 (or even 0.20) was due to the expectation that there would be a significant number of associations among diseases due to chance . Therefore, a more permissive threshold was established. On the other hand, despite the fact that the depressive pattern comprised only two diseases , this pattern has been previously identified in the literature Although several hypothesis have been put forward on the pathophysiological processes underlying the five multimorbidity patterns brought to light in this study, the former must be interpreted with the necessary caution since the study design  does not allow to establish the sequence in which diseases cluster within a pattern. Longitudinal studies would be required to corroborate the suggested causal associations as well as to help elucidate those disease associations that could not be explained in the present study.As stated earlier, this study was based on information that was recorded in the primary care electronic medical record system during medical visits. Although there are many benefits of this methodology, it can also limit the data. The workload of healthcare professionals and the structure of the applied diagnostic coding system (i.e. ICPC) often lead certain information regarding disease history not to be recorded in the individual patient medical histories. Therefore, the frequencies of many diseases are often underestimated. We suspect that this may have occurred for smoking, which is systematically underreported in a population with a very high prevalence of smokers A potential overrepresentation of certain diagnoses may exist when these are associated with other diseases for which treatment protocols recommend periodic health reviews. In other words, the higher frequency of visits by patients with these diseases would affect the likelihood that associated diseases were diagnosed . To avoid this bias, future studies should be based on the entire population rather than solely on those users of the primary care services.It is important to note that this work focused on chronic diseases. Although this may ensure comparability with other large studies across different international contexts, future research should consider including the whole range of diseases seen in patients. This would be especially true where the boundaries between “chronic” and “acute” diseases are not always clear, as was demonstrated by Starfield Although the different age groups were defined according to the expected biological homogeneity of individuals among groups, the selected thresholds could have influenced the nature of the obtained multimorbidity patterns. The use of different and/or narrower age groups may be advisable in future studies.To conclude with the potential limitations of this study, it should be noted that this study focused on the occurrence and the simultaneous association of diseases that were defined and registered from the perspective of the professionals caring for the patient and not by the patient him/herself. It is possible that many of the disease manifestations affecting the quality of life of the patient are not met by the defined criteria. Understanding the diseases from this perspective would require complementary methodological approaches that are beyond the scope of this work.It is difficult to compare these results with those of other studies because of differences in the disease inclusion criteria, the study populations and the data sources used. This study was also the first to extend the analysis to age groups under 65. The study by Schäfer et al. Despite the significance of multimorbidity, especially in older individuals, the scientific evidence provided by the clinical practice guidelines is not appropriate for patients with multiple diseases From the standpoint of healthcare management, strong and developed primary care is the best solution to the complex needs of patients with multimorbidity Moreover, the importance of other approaches beyond those based on health services, which are needed to ensure the health of the population, should be stressed. For example, the promotion of a healthy lifestyle is closely linked to a decline in the incidence of obesity Finally, a change in the focus of etiologic research is required for the study of diseases and their relationship to joint presentations, and an analysis of underlying factors, including pathophysiological, genetic, iatrogenic and/or socioeconomic factors should be promoted.The results of this work have demonstrated that the existence of non-random associations between chronic diseases is a reality for the entire population, not only the elderly.These disease associations give rise to clinically consistent multimorbidity patterns that affect a significant proportion of the population. Most importantly, when studying the lifetime disease process, there are underlying pathophysiological phenomena upon which action can be taken both from a clinical, individual-level perspective and from a public health or population-level perspective.Knowledge regarding the main disease patterns and their evolution with age should facilitate the design of tools, such as clinical practice guidelines, treatment protocols for patients with multimorbidity and healthcare information systems with alarm signals to monitor for the duplication of visits and diagnostic tests, the incidence of polypharmacy and potential adverse drug reactions, inappropriate hospitalisations and even mortality.All information available in the health systems should be properly managed to maximise the individual attention given to these patients and to ensure the efficient use of resources. This will positively impact the overall health of the population.The integration of information is a basic strategy that should be accompanied by structural and functional measures that promote coordination between different actors and levels of the care and that ensure safe and adequate communication among the professionals who care for such patients.Multimorbidity is a public health problem that must be considered by the planning and organisational frameworks of the health system. This work aimed to provide clinically relevant information to improve this process.Table S1Prevalence (%) of chronic EDCs (Expanded Diagnosis Cluster) within each age and sex group.(DOCX)Click here for additional data file.


Measurement of malaria burden is fraught with complexity, due to the natural history of the disease, delays in seeking treatment or failure of case management. Attempts to establish an appropriate case definition for a malaria episode has often resulted in ambiguities and challenges because of poor information about treatment seeking, patterns of infection, recurrence of fever and asymptomatic infection. While the primary reason for treating malaria is to reduce disease burden, the effects of treatment are generally ignored in estimates of the burden of malaria morbidity, which are usually presented in terms of numbers of clinical cases or episodes, with the main data sources being reports from health facilities and parasite prevalence surveys. The use of burden estimates that do not consider effects of treatment, leads to under-estimation of the impact of improvements in case management. Official estimates of burden very likely massively underestimate the impact of the roll-out of ACT as first-line therapy across Africa. This paper proposes a novel approach for estimating burden of disease based on the point prevalence of malaria attributable disease, or equivalently, the days with malaria fever in unit time. The technique makes use of data available from standard community surveys, analyses of fever patterns in malaria therapy patients, and data on recall bias. Application of this approach to data from Zambia for 2009–2010 gave an estimate of 2.6  malaria attributable fever days per child-year. The estimates of recall bias, and of the numbers of days with illness contributing to single illness recalls, could be applied more generally. To obtain valid estimates of the overall malaria burden using these methods, there remains a need for surveys to include the whole range of ages of hosts in the population and for data on seasonality patterns in confirmed case series. Malaria continues to be a major cause of disability and death in countries where it is endemic Plasmodium falciparum malaria infection can last for many months, causing recurring clinical attacks interspersed with asymptomatic periods P. falciparum. In this figure, the single (untreated) infection gives rise to five periods of high parasitaemia. The first two of these are each associated with several bouts of fever indicated by the black bars at the top  This sporadic pattern of clinical symptoms of untreated disease complicates the definition of clinical incidence. For many infectious diseases, for instance influenza, each incident infection leads to one and only one period of illness, or episode. For such diseases, the burden can thus be estimated from the incidence of disease and the duration of episodes, with an appropriate weighting used to convert numbers of episodes into disability adjusted life years (DALYs) or quality adjusted life years (QALYs). By contrast, with malaria, one incident infection may lead to multiple periods of illness  estimate of 225 million cases in 2009 P. falciparum prevalence determined from surveys are combined with information on climate suitability for malaria transmission and population density in order to classify populations according to endemicity level. Clinical incidence values are assigned to each endemicity level based on estimates of the numbers of events recorded in longitudinal surveys of febrile malaria episodes in children, detected either actively or passively In most of sub-Saharan Africa, presumptive treatment (without prior diagnosis) has been the norm, and the number of treatments is a poor measure of the number of episodes  and cannAn alternative to these approaches is to use recalls of illness from cross-sectional surveys carried out in the community. An increasing body of data is available from demographic and health surveys (DHS), multiple indicator cluster surveys (MICS), and malaria indicator surveys (MIS), which include asking respondents to provide a recall of illness during the previous two weeks for each of their children. This paper shows how these data can be used to obtain improved estimates of the malaria disease burden.Four types of data were used to illustrate the methods:Daily fever prevalence. For the analysis of bias in recall of fever, data of Feikin and colleagues Malaria therapy data. Fever patterns in untreated and inadequately treated malaria patients were analyzed using the data of 330 neurosyphilis patients treated with P. falciparum in the National Institutes of Health laboratories in Columbia, South Carolina and Milledgeville, Georgia in the United States of America Malaria Indicator Survey data. Data on history of fever in the last fourteen days from the 2010 MIS from Zambia Health Management Information System records. Counts of diagnosed malaria patients from all health facilities in Luangwa District, Zambia extracted from the national HMIS database.Two-week morbidity recalls do not elicit complete information about illness during the reference period because respondents may forget or conceal information. The usual survey procedures do not directly provide any information about recall bias but it can be estimated when respondents are asked  about illness on each distinct day during the reference period. This is because independence of the timing of the survey and the illness justifies the presumption that variations in fever rates by recall lag reflect recall bias.i days prior to interview is iF is the fever prevalence recorded in the survey for the single day, i days prior to interview.  in each of these intervals was evaluated as though the patient had been interviewed at j = 14. Each day of fever was assumed recalled with probability j and j.Naively, the probability that a survey respondent reports fever, conditional on fever having occurred during a two week reference period might be thought to be ple days , and theple days , so the P. falciparum histidine rich protein 2 (PfHRP2) measure the period prevalence of malaria infections. As PfHRP2 persists in the bloodstream for up to a month following parasite clearance PfHRP2 positivity (unlike blood slide positivity) can be used to detect recalled (as well as current) malaria fevers.MIS use two-week reference periods to elicit histories of both illness and of treatment. The signs and symptoms of malaria are common to those of other diseases, so interviews alone perform poorly in assigning malaria as the cause of illness. To determine the proportion of recalled illness that is due to malaria, the results of parasitological testing are needed in addition to clinical data. In fourteen day recall surveys, individuals who report malaria fever are not necessarily parasitaemic at the time of the survey. However, rapid diagnostic tests (RDTs) based on the presence of the Some RDT-positive fevers are of non-malaria etiology, but have incidental parasitaemia. The proportion of fevers that are of malaria etiology  can be estimated from the excess risk of fever among parasitaemic individuals, and must also be considered in the analysis.Two approaches were used to obtain estimates of the period prevalence of malaria attributable fever, taking into account all the above considerations:ep, the period prevalence of reported fever, fp, and the relative risk of fever associated with malaria, RR, in each case without accounting for reporting bias, using formulae given in PAF, and period prevalence of reported malaria attributable fever, mfp, were then obtained by substituting the estimates of e, pfp, and RR into further formulae given in mfp thus obtained was then mapped on an estimate of the period prevalence of malaria fever allowing for reporting bias, r  fourteen day intervals with fever days are estimated to have been  recalled as containing one or more fever bouts, corresponding to 19% underreporting and a value of r = 0.81 . This vaThe probability that fever is recalled is further complicated by the effects of treatment. While et = 0.187).The proportion of fever recalls mentioning treatment has a non-linear relationship with the daily probability of treatment, because recurrent fevers provide multiple opportunities to treat, so even a modest rate of treatment per day of fever will result in a very high proportion of recalled fevers being treated. The simulation of surveys based on the malaria therapy data suggests that the 34% of fever recalls in the Zambian MIS data that reported treatment  correspo = 8.1% .p, m, and n. All these estimates were conditional on the distribution of r estimated from the Asembo data on recall probabilities, and on the analysis of total fever days in the malaria therapy data   was obtaapy data . The anaThe number of days with fever associated with each reference period reported to have fever, depends on the treatment rate. As treatment rates increase, the number of days with fever corresponding to each report decreases, since an increasing proportion is averted by the treatments, until in the limiting case of 100% prompt and effective treatment, each report corresponds to exactly one day with fever . In the The recalled treatment rate for a positive RDT together with a fever estimated from the national level data is 34.0% (right hand column of This compares with an incidence estimate of 1.5 million cases in the year 2009 (confirmed and probable) for the 2.3 million children under five years old in Zambia given in the World Malaria Report Quantification of malaria in an area can have various objectives. This paper focuses on the assessment of disease burden, defined in terms of experience of illness. This is needed for assessing progress in improving health and for cost-effectiveness analyses of intervention programs. Disease burden quantification requires population-based data, and community-based measures of parasite prevalence and anaemia prevalence, available from MIS, are recommended as morbidity indicators for national malaria control programs in the monitoring and evaluation (M&E) toolkit of the Global Fund to fight AIDS, TB and Malaria (GFATM) In this paper, fever recalls from MIS surveys are proposed as the primary source for estimates of malaria morbidity burden. This approach contrasts with the use of HMIS data as the primary source for estimates of disease burden. From the clinical perspective, it may be good enough to identify an “episode” or “case” when an individual presents to a health facility with febrile illness and detectable parasitaemia. Activity statistics derived directly from such case registration are useful for commodity forecasting and managing clinical workloads, and may also be suitable as outcomes in intervention trials where the goal is simply to detect a difference between two or more arms, but these are only a subset of the reasons for quantifying the amount of malaria, and in particular are not the same as assessment of disease burden. Other possible objectives include assessment of the level of transmission  data are used as the primary source of data on disease burden, they need adjustments. Firstly, the calculations must correct for sick individuals who do not report to the health facility. Making this adjustment is challenging, because untreated malaria attributable fevers that are invisible in the statistics have different durations from the treated fevers that are visible in the statistics. Adjusting for this is especially challenging when there are changes in access to care, since improved access reduces disease burden non-linearly while increasing levels of activity. Additionally, it is not clear how to adjust activity statistics to allow for the benefits of improvements in case management that replace failing treatments and reduce the duration of illness, such as the roll-out of ACT as first-line therapy across Africa. Lastly, activity statistics do not distinguish changes in diagnostic accuracy from changes in epidemiology.Thus, until recently in places highly endemic for malaria, a febrile patient with a viral infection was generally presumptively treated for malaria and recorded as a malaria case. Control of malaria and the introduction of parasitological diagnoses mean that such patients are now less likely to appear in malaria statistics. Rather, they are more likely to be classed as respiratory infections. This is appropriate, insofar as these statistics measure the activity of the health system, but the introduction of diagnostic tests for malaria has not resulted in a larger burden of disease due to respiratory infections. Similarly, the proportion of non-malaria fever patients with incidental parasitaemia declines when malaria transmission is reduced. These patients should be treated for malaria, and hence contribute to activity statistics, but the burden of disease associated with them should be assigned to the etiological agent causing the fever, in such cases not malaria, so that changes in malaria burden estimate should be unaffected by the number of such patients. In general therefore, the use of activity statistics to measure burden can give a quite false idea of the importance of malaria relative to other illnesses and may misrepresent the relative contributions of preventive and curative interventions to improvements in public health.Fever recalls from surveys provide a direct measure of morbidity, are increasingly widely available, and in some situations data have been validated as comparative morbidity measures The validity of combining these datasets can be questioned, especially because of the assumption that the patterns of fever in African children parallel those in malaria therapy patients. Superficially, patterns observed in closely monitored Gambian children Some of the data limitations could be addressed by improvements in survey design. First, cross-sectional surveys of malaria illness and treatment-seeking need to include questions on history of fever and measure parasitaemia in all age groups, not just in children under five: as malaria control efforts are scaled-up and transmission falls, malaria illness tends to shift into older age groups Measurement of malaria burden is fraught with complexity mainly due to the natural history of the disease and to sub-optimal health facility utilization which means that treatment is often delayed or not sought. Definitions of malaria episodes are either ambiguous or difficult to use because good information about patterns of infection, recurrence of fever or asymptomatic infection is rarely available.This paper suggests that the point prevalence of malaria attributable disease, or equivalently, the days with malaria fever in unit time, should be used as a measure of burden. This avoids the problem of defining a malaria episode, and suggests that burden can, in principle, be estimated in an unbiased way from data that are already collected in national MIS, combined with data on seasonality. The estimates used in this paper of recall bias, and of the numbers of days with illness contributing to single illness recalls, could be applied more generally.It is hoped that this work will stimulate a dialogue on how to improve measurement of the burden of uncomplicated malaria.Figure S1Mean duration of illness per episode depending on treatment in malaria therapy patients. The mean number of fever days per episode (duration of illness) depending on the probability of treatment of fever and length of the health system memory for treated episodes (a & d) and untreated episodes (b & e), and the probability of an episode being treated (c & f), for daily probability of treatment (a–c), and five-daily probability of treatment (d–f). Health system memory length (days): black 5, red 10, green 15, dark blue 20, light blue 25, magenta 30, yellow 35, grey 40. Smoothing splines were drawn through scattered points, which were averages of 100 repeated simulations.(TIF)Click here for additional data file.Figure S2Probability in micro simulation models of an episode being treated. The probability of an episode being treated is plotted against the treatment seeking probability per five-day time step, with a 15 day health system memory. The green line is copied from R0674 (uncorrelated heterogeneities in access to treatment and susceptibility to co-morbidity) and R0678 (heterogeneity in access to treatment), are excluded because at high treatment coverage levels, there is an upper limit to the level of heterogeneity.(TIF)Click here for additional data file.Text S1Simulation modeling of the burden of uncomplicated malaria.(DOC)Click here for additional data file.Script S1WinBUGS code for estimating parameters of branching process.(DOC)Click here for additional data file.


Environmental Health Perspectives (EHP) contains several articles in the field of toxicology and includes the poster Benchmarks in Toxicology, which delineates the most significant accomplishments in the field, from Phillipus Aurolus Paracelsus, the sixteenth-century scientist considered to be the “father of toxicology,” to today’s cutting-edge technologies and initiatives that are enabling the current radical transformation of the discipline. EHP’s March podcast features an interview with Peter Goering, a research toxicologist at the U.S. Food and Drug Administration and secretary of the Society of Toxicology. In the interview, he discusses how the benchmarks were selected and provides more details about specific benchmarks.The National Institute of Environmental Health Sciences (NIEHS) joins with the entire environmental health sciences community in celebrating the 50th anniversary of the Society of Toxicology (SOT). This issue of The SOT was founded on 6 March 1961 by a visionary group of nine founders who were joined by 183 charter members. Today the SOT is a global organization with > 6,500 members from all over the world. It is a broad tent, with everyone in the field welcomed and encouraged to participate, including basic scientists, regulators, academics, industry professionals, government officials, consultants, and representatives from non-governmental organizations. With such a richly diverse membership, many different viewpoints from many different types of scientists are heard, which makes for a robust, healthy scientific dialogue. The SOT’s strong emphasis on mentoring and education programs, along with its recruitment of younger members into interesting roles and committee assignments in the organization, helps to ensure commitment to the field’s health by the next generation of toxicologists.The SOT has long been intensely devoted to building for the future of toxicology and the professional development of its membership. For example, the SOT currently has 26 specialty sections focusing on specific areas of toxicology. These science-based programs are complemented by 27 elected and appointed committees, subcommittees, and task forces; 18 regional chapters; and 6 Special Interest Groups (SIGs). The SIGs, which include the American Association of Chinese in Toxicology, the Association of Scientists of Indian Origin, the Hispanic Organization of Toxicologists, the Korean Toxicologists Association in America, Toxicologists of African Origin, and Women in Toxicology, promote the diversity and inclusiveness of the organization by recruiting toxicologists who share a common interest in toxicological research issues germane to their cultures and communities. The SOT also maintains a global perspective, playing a major role in the International Union of Toxicology (IUTOX) as one of the member societies on the IUTOX executive committee.Over the past 50 years the SOT has played a key role in advancing the science of toxicology as it has evolved from a science devoted to studying poisons and adverse effects of chemical exposures to a science devoted to studying safety. As toxicology has changed from a descriptive, observational discipline to one with an emphasis on predictive power and protection of public health, the SOT has been at the forefront of this profound reorientation.I first joined the SOT in 1982. Since then I have had the honor of serving as the society’s president (2004–2005) and in several other leadership roles. So it should come as no surprise that the SOT is near and dear to my heart, and I can confidently state that it is an asset to of all of us at the NIEHS and the National Toxicology Program (NTP).For me, the SOT Annual Meeting has always been an essential conference to attend to hear about the newest findings and newest areas of research in toxicology. I’ve always enjoyed the plenary sessions, the special lectures, such as the Medical Research Council keynote lectures, and the many symposia focusing on new information in various areas. I am always inspired by the workshops and roundtables that take place at the meeting; the formats of those sessions facilitate positive and open discussion between people with differing views in a nonthreatening atmosphere.The quality of the science presented at the meeting is extremely high. I would especially encourage younger scientists in the field to attend and make the most of their experience. There are numerous opportunities for junior researchers to meet and interact with more senior scientists, particularly at the poster sessions and mentoring programs. As I can testify from personal experience, those interactions can have long-lasting benefits to your scientific and career success.EHP.I am proud that the NIEHS and NTP have been a major presence at the SOT Annual Meeting and ToxExpo in recent years. In 2010, we hosted > 30 sessions and presented > 60 posters. We also inaugurated an innovative service called SOT Live Update, which provided nearly 100 up-to-the-minute observations about conference events and activities online and on Twitter. And of course, we had a large booth at the ToxExpo where conference goers could pick up the latest issue of http://www.niehs.nih.gov) and on Twitter (http://twitter.com/NIEHS). That way, those of you who cannot attend will still be able to get the flavor of this most important event on the toxicology calendar.At this year’s 50th Annual Meeting, 6–10 March in Washington, DC, we will once again lead the proceedings with investigators and program officers presenting many posters and sessions, including sessions to answer questions about applying for grants. We will host an exhibit booth and provide live online updates by conference participants (including me), which will be continuously posted on the NIEHS website (This year’s meeting is especially significant, of course. With a variety of terrific activities planned to fete the SOT’s 50th anniversary, it will literally be a once-in-a-lifetime experience. I can’t wait to join our friends and colleagues as we gather to recognize 50 remarkable years of SOT. It will be a great opportunity to fondly celebrate the past as we eagerly anticipate the future.See you, I hope, in DC!


Burns are a worldwide problem. The incidence of severe burns has been higher than the combined incidence of tuberculosis and HIV infections. Throughout history there have been many different treatments prescribed for burns. The Canon is the masterpiece of Avicenna’s medical books. The Canon includes a description of 785 simple drugs. Avicenna believed in burn treatment, which follows two goals. The first goal is prevention of blistering and the second goal is treatment of the burn wound after it has created blisters, cold drugs are suitable for the first goal and dry drugs with moderate in cold and hot qualities are better for second goal, this study reviewed remedies for burn wounds in Canon. Avicenna, The Canon of Medicine. New York: AMS Press; 1973. ISBN: 0-404-11231-5. Number of Pages: 641.Since man first learned to make fire, burns and scalds have been one of the most common of his injuries . Despiteth century, longer than any other medical work  has an important place, and forms the basis of pathology, diagnosis and treatment . The bodThis project evaluated the influence of medicinal plants on burn, and this article covers a section of the finding. To our knowledge, it is the first article in our country, which concerns this subject.In this study the Arabic Canon was searched for the Arabic term of “Hargh” meaning burn, for herbal drugs which are effective on burn wound healing. Next, the term was rechecked in the English translated Canon   and theiIbn Sina began the second book  with a discussion on the nature and quality of drugs or temperament . In the forth book, he explained kinds of injuries and wounds and their treatments. He also explained fire burns  and scalds  and their remedies. He believed that burn treatment show follow two goals. The first goal is prevention of blistering and the second goal is treatment of burn wounds after blisters have developed . He beliMyrtus communis L. or “Khubbazi” Malva sylvestris L, and when the wound has more discharge it is better to use herbal drugs by dryness temperament and so on, therefore, treatment should be selected based upon the type of wound. There are many effective remedies in Iranian Traditional Medicine for wound healing. We hope soon these herbs are clinically tested and widely available to people for burn wound treatment.Ibn Sina, is one of the most famous Persian physicians and Scientist in Iran, and in the world and Canon is his medicinal book. Although there are many studies on Avicenna and his Canon, this is the first study focusing simple herbal drugs in Canon for burn wound healing. In this study second book of Canon was searched for burn remedies, and 28 simple herbal drugs take. Avicenna described burn treatment following two goals. The first goal is prevention of blistering, and the second goal is treatment of burn wound after blister formation . He beli