Epidemiologic transition in northern Angola: discussion of cumulative results from CISA (Health Research Centre of Angola)

The 41 years of armed conflict (1961 to 2002) resulted in a poor development of the health care and education infrastructures, and forced the relocation of people to safer places, namely major urban cities like Luanda. This phase was characterized by typical demographic, nutritional and epidemiological profiles. With the end of this period Angola has been repeatedly ranked as one of the three fastest growing economies in the world, and along with the social stabilization and globalization, the country is facing the introduction of new medical technologies, improvement of health sys-tems and services, better access to them, and overall better quality of life. These changes could also be translating into socio-cultural, demographic and nutritional changes which in turn may leading to changes in the epidemiological profile of the country. Thus, the emergence of non-communicable diseases are likely to become an increasingly im-portant public health problem in Angola. Also, considering that several infectious diseases persist, our weakened health system will have to face a double burden. Thus, disease surveillance data on non-communicable diseases to determine their prevalence and impact, along with the major behavioural risk factors like consumption of tobacco, alcohol, diets and physical inactivity are urgently needed.

CardioBengo study protocol: a population based cardiovascular longitudinal study in Bengo Province, Angola

Background: Cardiovascular diseases and other non-communicable diseases are major causes of morbidity and mortality, responsible for 38 million deaths in 2012, 75 % occurring in low- and middle-income countries. Most of these countries are facing a period of epidemiological transition, being confronted with an increased burden of non-communicable diseases, which challenge health systems mainly designed to deal with infectious diseases. With the adoption of the World Health Organization “Global Action Plan for the Prevention and Control of non-communicable diseases, 2013–2020”, the national dimension of risk factors for non-communicable diseases must be reported on a regular basis. Angola has no national surveillance system for non-communicable diseases, and periodic population-based studies can help to overcome this lack of information. CardioBengo will collect information on risk factors, awareness rates and prevalence of symptoms relevant to cardiovascular diseases, to assist decision makers in the implementation of prevention and treatment policies and programs. Methods: CardioBengo is designed as a research structure that comprises a cross-sectional component, providing baseline information and the assembling of a cohort to follow-up the dynamics of cardiovascular diseases risk factors in the catchment area of the Dande Health and Demographic Surveillance System of the Health Research Centre of Angola, in Bengo Province, Angola. The World Health Organization STEPwise approach to surveillance questionnaires and procedures will be used to collect information on a representative sex-age stratified sample, aged between 15 and 64 years old. Discussion: CardioBengo will recruit the first population cohort in Angola designed to evaluate cardiovascular diseases risk factors. Using the structures in place of the Dande Health and Demographic Surveillance System and a reliable methodology that generates comparable results with other regions and countries, this study will constitute a useful tool for the surveillance of cardiovascular diseases. Like all longitudinal studies, a strong concern exists regarding dropouts, but strategies like regular visits to selected participants and a strong community involvement are in place to minimize these occurrences.

Main causes of death in Dande, Angola: results from verbal autopsies of deaths occurring during 2009–2012

bACKGROUND - The Dande Health and Demographic Surveillance System (HDSS) located in Bengo province, Angola, covers nearly 65,500 residents living in approximately 19,800 households. This study aims to describe the main causes of deaths (CoD) occurred within the HDSS, from 2009 to 2012, and to explore associations between demographic or socioeconomic factors and broad mortality groups (Group I-Communicable diseases, maternal, perinatal and nutritional conditions; Group II-Non-communicable diseases; Group III-Injuries; IND-Indeterminate). Methods - Verbal Autopsies (VA) were performed after death identification during routine HDSS visits. Associations between broad groups of CoD and sex, age, education, socioeconomic position, place of residence and place of death, were explored using chi-square tests and fitting logistic regression models. Results - From a total of 1488 deaths registered, 1009 verbal autopsies were performed and 798 of these were assigned a CoD based on the 10th revision of the International Classification of Diseases (ICD-10). Mortality was led by CD (61.0%), followed by IND (18.3%), NCD (11.6%) and INJ (9.1%). Intestinal infectious diseases, malnutrition and acute respiratory infections were the main contributors to under-five mortality (44.2%). Malaria was the most common CoD among children under 15 years old (38.6%). Tuberculosis, traffic accidents and malaria led the CoD among adults aged 15–49 (13.5%, 10.5 % and 8.0% respectively). Among adults aged 50 or more, diseases of the circulatory system (23.2%) were the major CoD, followed by tuberculosis (8.2%) and malaria (7.7%). CD were more frequent CoD among less educated people (adjusted odds ratio, 95% confidence interval for none vs. 5 or more years of school: 1.68, 1.04–2.72). Conclusion - Infectious diseases were the leading CoD in this region. Verbal autopsies proved useful to identify the main CoD, being an important tool in settings where vital statistics are scarce and death registration systems have limitations.

Symbolic dynamics and renormalization of non-autonomous k periodic dynamical systems

The purpose of this paper was to introduce the symbolic formalism based on kneading theory, which allows us to study the renormalization of non-autonomous periodic dynamical systems.

The use of non-standard CT conversion ramps for Monte Carlo verification of 6 MV prostate IMRT plans

Monte Carlo (MC) dose calculation algorithms have been widely used to verify the accuracy of intensity-modulated radiotherapy (IMRT) dose distributions computed by conventional algorithms due to the ability to precisely account for the effects of tissue inhomogeneities and multileaf collimator characteristics. Both algorithms present, however, a particular difference in terms of dose calculation and report. Whereas dose from conventional methods is traditionally computed and reported as the water-equivalent dose (Dw), MC dose algorithms calculate and report dose to medium (Dm). In order to compare consistently both methods, the conversion of MC Dm into Dw is therefore necessary. This study aims to assess the effect of applying the conversion of MC-based Dm distributions to Dw for prostate IMRT plans generated for 6 MV photon beams. MC phantoms were created from the patient CT images using three different ramps to convert CT numbers into material and mass density: a conventional four material ramp (CTCREATE) and two simplified CT conversion ramps: (1) air and water with variable densities and (2) air and water with unit density. MC simulations were performed using the BEAMnrc code for the treatment head simulation and the DOSXYZnrc code for the patient dose calculation. The conversion of Dm to Dw by scaling with the stopping power ratios of water to medium was also performed in a post-MC calculation process. The comparison of MC dose distributions calculated in conventional and simplified (water with variable densities) phantoms showed that the effect of material composition on dose-volume histograms (DVH) was less than 1% for soft tissue and about 2.5% near and inside bone structures. The effect of material density on DVH was less than 1% for all tissues through the comparison of MC distributions performed in the two simplified phantoms considering water. Additionally, MC dose distributions were compared with the predictions from an Eclipse treatment planning system (TPS), which employed a pencil beam convolution (PBC) algorithm with Modified Batho Power Law heterogeneity correction. Eclipse PBC and MC calculations (conventional and simplified phantoms) agreed well (<1%) for soft tissues. For femoral heads, differences up to 3% were observed between the DVH for Eclipse PBC and MC calculated in conventional phantoms. The use of the CT conversion ramp of water with variable densities for MC simulations showed no dose discrepancies (0.5%) with the PBC algorithm. Moreover, converting Dm to Dw using mass stopping power ratios resulted in a significant shift (up to 6%) in the DVH for the femoral heads compared to the Eclipse PBC one. Our results show that, for prostate IMRT plans delivered with 6 MV photon beams, no conversion of MC dose from medium to water using stopping power ratio is needed. In contrast, MC dose calculations using water with variable density may be a simple way to solve the problem found using the dose conversion method based on the stopping power ratio.