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      Modelling historical changes in the force-of-infection of Chagas disease to inform control and elimination programmes: application in Colombia

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          Abstract

          Background

          WHO's 2020 milestones for Chagas disease include having all endemic Latin American countries certified with no intradomiciliary Trypanosoma cruzi transmission, and infected patients under care. Evaluating the variation in historical exposure to infection is crucial for assessing progress and for understanding the priorities to achieve these milestones.

          Methods

          Focusing on Colombia, all the available age-structured serological surveys (undertaken between 1995 and 2014) were searched and compiled. A total of 109 serosurveys were found, comprising 83 742 individuals from rural (indigenous and non-indigenous) and urban settings in 14 (out of 32) administrative units (departments). Estimates of the force-of-infection (FoI) were obtained by fitting and comparing three catalytic models using Bayesian methods to reconstruct temporal and spatial patterns over the course of three decades (between 1984 and 2014).

          Results

          Significant downward changes in the FoI were identified over the course of the three decades, and in some specific locations the predicted current seroprevalence in children aged 0–5 years is <1%. However, pronounced heterogeneity exists within departments, especially between indigenous, rural and urban settings, with the former exhibiting the highest FoI (up to 66 new infections/1000 people susceptible/year). The FoI in most of the indigenous settings remain unchanged during the three decades investigated. Current prevalence in adults in these 15 departments varies between 10% and 90% depending on the dynamics of historical exposure.

          Conclusions

          Assessing progress towards the control of Chagas disease requires quantifying the impact of historical exposure on current age-specific prevalence at subnational level. In Colombia, despite the evident progress, there is a marked heterogeneity indicating that in some areas the vector control interventions have not been effective, hindering the possibility of achieving interruption by 2020. A substantial burden of chronic cases remains even in locations where serological criteria for transmission interruption may have been achieved, therefore still demanding diagnosis and treatment interventions.

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          Most cited references31

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          Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010.

          Reliable and timely information on the leading causes of death in populations, and how these are changing, is a crucial input into health policy debates. In the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010), we aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex. We attempted to identify all available data on causes of death for 187 countries from 1980 to 2010 from vital registration, verbal autopsy, mortality surveillance, censuses, surveys, hospitals, police records, and mortuaries. We assessed data quality for completeness, diagnostic accuracy, missing data, stochastic variations, and probable causes of death. We applied six different modelling strategies to estimate cause-specific mortality trends depending on the strength of the data. For 133 causes and three special aggregates we used the Cause of Death Ensemble model (CODEm) approach, which uses four families of statistical models testing a large set of different models using different permutations of covariates. Model ensembles were developed from these component models. We assessed model performance with rigorous out-of-sample testing of prediction error and the validity of 95% UIs. For 13 causes with low observed numbers of deaths, we developed negative binomial models with plausible covariates. For 27 causes for which death is rare, we modelled the higher level cause in the cause hierarchy of the GBD 2010 and then allocated deaths across component causes proportionately, estimated from all available data in the database. For selected causes (African trypanosomiasis, congenital syphilis, whooping cough, measles, typhoid and parathyroid, leishmaniasis, acute hepatitis E, and HIV/AIDS), we used natural history models based on information on incidence, prevalence, and case-fatality. We separately estimated cause fractions by aetiology for diarrhoea, lower respiratory infections, and meningitis, as well as disaggregations by subcause for chronic kidney disease, maternal disorders, cirrhosis, and liver cancer. For deaths due to collective violence and natural disasters, we used mortality shock regressions. For every cause, we estimated 95% UIs that captured both parameter estimation uncertainty and uncertainty due to model specification where CODEm was used. We constrained cause-specific fractions within every age-sex group to sum to total mortality based on draws from the uncertainty distributions. In 2010, there were 52·8 million deaths globally. At the most aggregate level, communicable, maternal, neonatal, and nutritional causes were 24·9% of deaths worldwide in 2010, down from 15·9 million (34·1%) of 46·5 million in 1990. This decrease was largely due to decreases in mortality from diarrhoeal disease (from 2·5 to 1·4 million), lower respiratory infections (from 3·4 to 2·8 million), neonatal disorders (from 3·1 to 2·2 million), measles (from 0·63 to 0·13 million), and tetanus (from 0·27 to 0·06 million). Deaths from HIV/AIDS increased from 0·30 million in 1990 to 1·5 million in 2010, reaching a peak of 1·7 million in 2006. Malaria mortality also rose by an estimated 19·9% since 1990 to 1·17 million deaths in 2010. Tuberculosis killed 1·2 million people in 2010. Deaths from non-communicable diseases rose by just under 8 million between 1990 and 2010, accounting for two of every three deaths (34·5 million) worldwide by 2010. 8 million people died from cancer in 2010, 38% more than two decades ago; of these, 1·5 million (19%) were from trachea, bronchus, and lung cancer. Ischaemic heart disease and stroke collectively killed 12·9 million people in 2010, or one in four deaths worldwide, compared with one in five in 1990; 1·3 million deaths were due to diabetes, twice as many as in 1990. The fraction of global deaths due to injuries (5·1 million deaths) was marginally higher in 2010 (9·6%) compared with two decades earlier (8·8%). This was driven by a 46% rise in deaths worldwide due to road traffic accidents (1·3 million in 2010) and a rise in deaths from falls. Ischaemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lower respiratory infections, lung cancer, and HIV/AIDS were the leading causes of death in 2010. Ischaemic heart disease, lower respiratory infections, stroke, diarrhoeal disease, malaria, and HIV/AIDS were the leading causes of years of life lost due to premature mortality (YLLs) in 2010, similar to what was estimated for 1990, except for HIV/AIDS and preterm birth complications. YLLs from lower respiratory infections and diarrhoea decreased by 45-54% since 1990; ischaemic heart disease and stroke YLLs increased by 17-28%. Regional variations in leading causes of death were substantial. Communicable, maternal, neonatal, and nutritional causes still accounted for 76% of premature mortality in sub-Saharan Africa in 2010. Age standardised death rates from some key disorders rose (HIV/AIDS, Alzheimer's disease, diabetes mellitus, and chronic kidney disease in particular), but for most diseases, death rates fell in the past two decades; including major vascular diseases, COPD, most forms of cancer, liver cirrhosis, and maternal disorders. For other conditions, notably malaria, prostate cancer, and injuries, little change was noted. Population growth, increased average age of the world's population, and largely decreasing age-specific, sex-specific, and cause-specific death rates combine to drive a broad shift from communicable, maternal, neonatal, and nutritional causes towards non-communicable diseases. Nevertheless, communicable, maternal, neonatal, and nutritional causes remain the dominant causes of YLLs in sub-Saharan Africa. Overlaid on this general pattern of the epidemiological transition, marked regional variation exists in many causes, such as interpersonal violence, suicide, liver cancer, diabetes, cirrhosis, Chagas disease, African trypanosomiasis, melanoma, and others. Regional heterogeneity highlights the importance of sound epidemiological assessments of the causes of death on a regular basis. Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
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            Chagas disease in Spain, the United States and other non-endemic countries.

            Due to recent trends in migration, there are millions of people from Chagas disease-endemic countries now living in North America, Europe, Australia and Japan, including thousands of people with Trypanosoma cruzi infection. Most infected individuals are not aware of their status. Congenital, transfusion- and/or transplant-associated transmission has been documented in the United States, Spain, Canada and Switzerland; most instances likely go undetected. High priorities include the implementation of appropriate screening, evaluation and clinical management, and better assessment of the true burden associated with this disease. 2009 Elsevier B.V. All rights reserved.
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              Epidemiology of Chagas disease in non endemic countries: the role of international migration

              Human infection with the protozoa Trypanosoma cruzi extends through North, Central, and South America, affecting 21 countries. Most human infections in the Western Hemisphere occur through contact with infected bloodsucking insects of the triatomine species. As T. cruzi can be detected in the blood of untreated infected individuals, decades after infection took place; the infection can be also transmitted through blood transfusion and organ transplant, which is considered the second most common mode of transmission for T. cruzi. The third mode of transmission is congenital infection. Economic hardship, political problems, or both, have spurred migration from Chagas endemic countries to developed countries. The main destination of this immigration is Australia, Canada, Spain, and the United States. In fact, human infection through blood or organ transplantation, as well as confirmed or potential cases of congenital infections has been described in Spain and in the United States. Estimates reported here indicates that in Australia in 2005-2006, 1067 of the 65,255 Latin American immigrants (16 per 1000) may be infected with T. cruzi, and in Canada, in 2001, 1218 of the 131,135 immigrants (9 per 1000) whose country of origin was identified may have been also infected. In Spain, a magnet for Latin American immigrants since the 2000, 5125 of 241,866 legal immigrants in 2003 (25 per 1000), could be infected. In the United States, 56,028 to 357,205 of the 7,20 million, legal immigrants (8 to 50 per 1000), depending on the scenario, from the period 1981-2005 may be infected with T. cruzi. On the other hand, 33,193 to 336,097 of the estimated 5,6 million undocumented immigrants in 2000 (6 to 59 per 1000) could be infected. Non endemic countries receiving immigrants from the endemic ones should develop policies to protect organ recipients from T. cruzi infection, prevent tainting the blood supply with T. cruzi, and implement secondary prevention of congenital Chagas disease.
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                Author and article information

                Journal
                BMJ Glob Health
                BMJ Glob Health
                bmjgh
                bmjgh
                BMJ Global Health
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2059-7908
                2017
                7 September 2017
                : 2
                : 3
                : e000345
                Affiliations
                [1 ] departmentDepartment of Infectious Disease Epidemiology, Faculty of Medicine (St Mary's campus) , Imperial College London , London, UK
                [2 ] departmentDepartment of Infectious Disease Epidemiology, London Centre for Neglected Tropical Disease Research (LCNTDR) , Imperial College London , London, UK
                [3 ] Grupode Parasitología—RED CHAGAS, Instituto Nacional de Salud , Bogotá, Colombia
                [4 ] departmentDepartment of Infectious Disease Epidemiology, Faculty of Medicine (St Mary's campus), Medical Research Council Centre for Outbreak Analysis and Modelling , School of Public Health, Imperial College London , London, UK
                [5 ] departmentDepartment of Infectious Disease Epidemiology, Faculty of Medicine (St Mary's campus) , Health Economics Group, School of Public Health, Imperial College London , London, UK
                [6 ] Grupo de Enfermedades Endemo-Epidémicas, Subdirección Enfermedades Transmisibles, Ministerio de Salud y Protección Social , Bogotá, Colombia
                [7 ] departmentCentro de Investigaciones en Enfermedades Tropicales (CINTROP) , Universidad Industrial de Santander , Piedecuesta, Colombia
                [8 ] Fundación Salud para el Trópico , SantaMarta, Colombia
                [9 ] Instituto Colombiano de Medicina Tropical, Universidad CES , Santa Martha, Colombia
                Author notes
                [Correspondence to ] Dr Zulma M Cucunubá; zulma.cucunuba@ 123456imperial.ac.uk
                Author information
                http://orcid.org/0000-0002-8165-3198
                Article
                bmjgh-2017-000345
                10.1136/bmjgh-2017-000345
                5680445
                29147578
                79bbfa70-cbf9-4a5a-bf99-aa8a097aa0cc
                © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

                This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

                History
                : 13 March 2017
                : 23 July 2017
                : 24 July 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001921, Public Health Research Programme;
                Funded by: FundRef http://dx.doi.org/10.13039/100007637, Departamento Administrativo de Ciencia, Tecnología e Innovación;
                Funded by: NTD-Modelling Consortium;
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Categories
                Research
                1506
                Custom metadata
                unlocked

                chagas disease,serology,mathematical modelling,cross-sectional survey,control strategies

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