Hello Juan,
since both HIV and HCV are chronic illnesses and do not resolve, prevalence from different points in time would be an acceptable measure of the disease burden. However, that being said, at the country level, the design and number of samples tested will have a very strong effect on the prevalence-especially since the transmission of these diseases is not homogeneous. Furthermore, because they are chronic the age of the individuals sampled is also important since as they age, people have a higher chance of being exposed over time. This is very important when trying to compare different countries to each other. This an age adjusted prevalence of HIV and HCV could be useful to assess the disease burden.
Thus is a great research topic, since both have common exposure pathways!
Hola Juan,
interesante pregunta.
habría que distinguir 2 tipos de poblaciones una de alto riesgo (los nacidos entre 1945 y 1964) y el resto de población (bajo riesgo).
Es importante conocer cual es número de individuos en España de cada grupo de riesgo. Habría que llevar a cabo un muestreo nacional en los centros de salud mediante llamada telefónica a los sujetos elegidos a participar en el estudio (el diseño del estudio se llama muestreo estratificado). Un diseño similar se ha hecho con el estudio diabetes en España en el que se ha identificado cual es la prevalencia de diabetes en la población española (puedes consultarlo en la revista Diabetologia).
Dear Juan,
In the Netherlands, all HIV/HCV coinfected patients are registered in a national database (report accessible via http://www.hiv-monitoring.nl/english/). These data could be used for such research purposes. As member of the HIV/HCV working group I can access the raw data for additional question.
Juan,
I agree with Joop, if you have a surveillance system in your country you can get annual incidence and mortality rates over time to see the burden of both HIV/HCV or each one of them separately
Análogamente...
Soriguer F, Goday A, Bosch-Comas A, Bordiú E, Calle-Pascual A, Carmena R,
Casamitjana R, Castaño L, Castell C, Catalá M, Delgado E, Franch J, Gaztambide S, Girbés J, Gomis R, Gutiérrez G, López-Alba A, Martínez-Larrad MT, Menéndez E,
Mora-Peces I, Ortega E, Pascual-Manich G, Rojo-Martínez G, Serrano-Rios M, Valdés S, Vázquez JA, Vendrell J. Prevalence of diabetes mellitus and impaired glucose regulation in Spain: the [email protected] Study. Diabetologia. 2012 Jan;55(1):88-93.
AIMS/HYPOTHESIS:
The [email protected] Study is the first national study in Spain to examine the prevalence of diabetes and impaired glucose regulation.
METHODS:
A population-based, cross-sectional, cluster sampling study was carried out, with target population being the entire Spanish population. Five thousand and seventy-two participants in 100 clusters (health centres or the equivalent in each region) were randomly selected with a probability proportional to population size. Participation rate was 55.8%. Study variables were a clinical and demographic structured survey, lifestyle survey, physical examination (weight, height, BMI, waist and hip circumference, blood pressure) and OGTT (75 g).
RESULTS:
Almost 30% of the study population had some carbohydrate disturbance. The overall prevalence of diabetes mellitus adjusted for age and sex was 13.8% (95% CI 12.8, 14.7%), of which about half had unknown diabetes: 6.0% (95% CI 5.4, 6.7%). The age- and sex-adjusted prevalence rates of isolated impaired fasting glucose (IFG), isolated impaired glucose tolerance (IGT) and combined IFG-IGT were 3.4% (95% CI 2.9, 4.0%), 9.2% (95% CI 8.2, 10.2%) and 2.2% (95% CI 1.7, 2.7%), respectively. The prevalence of diabetes and impaired glucose regulation increased significantly with age (p
Estimado Juan:
Realmente no existe un mejor diseño para estimar una carga de enfermedad, cualesquiera que sea.
Los diseños estan hehcos para respodener preguntas de investigacion y la seleccion del diseño, no el mejor, porque eso es muy dficil de decidir, esta orientado en buena medida por la escala de medicion que utilices en la variable respuesta o desenlace.
Por ello, para poder responder a tu pregunta, habria que conocer que pregunta quieres responder y como medias tu variable respuesta.
I will try to add some value to the topic by pointing out things that have not yet been discussed, but I need to disagree with those suggesting the use of surveillance systems. I have worked with one of those and know the pitfalls very well.
Surveillance is good for detecting trends, but not prevalence or burden estimates, because it really depends how many cases are out there undiagnosed. People can be asymptomatic and dont get tested, then you have no idea what are the hidden numbers. So prevelence survey by all means and as it has been pointed out, has to be representative of the population and age adjusted.
That being said, things might get expensive up to very expensive if we are talking about a nation-wide cohort study. As we typically have limited budgets, one thing to evaluate is the concept of anonymous unlinked testing of residual sera in different laboratories (you get of course different results, depending on the population this sera belongs to, for example army recruits or pregnant women vs. STI clinics visitors). Of course, it is ideal to get at least age (and hopefully gender) of the patients these sera belong to.
Such anonymous unlinked studies are then repeated yearly or every two years to see how the prevalence changes. The upside is patient consent is not always deemed necessary, so nobody can reject the test (those who reject the test have been evaluated to be more likely infected in some studies, as they fear learning the result due to past risk behaviour) - then you get more accurate number of what the real prevalence is. This is a good, relatively cheap method (the great burden of work has already been done), but relies on ethical approval from authorities, on good collaboration from the laboratories, keeping track of total numbers etc., not loosing sera in the fridge etc. and minimum information about the patients the sera belong to, so you can check how representative the sample is.
Again, your budget will probably determine on how many laboratories (and potential samples of population) you can include - all national laboratories performing these tests or a sample of them (sentinel vs. nation wide). If you have pregnant women or army recruits, these are only a proxy for population - remember they are also just a selected and potentially even healthier and much younger subpopulation.
There are many important points already raised in this discussion, so it is not necessary to repeat the key points. However, Juan asked about estimating national HIV/HCV coinfection rates. This presents an even larger challenge since the population rates for coinfection are exceeding low. Thus large numbers will need to be screened. In this case one possible source of data might be blood donor systems, either national or regional. Blood banks screen routinely for the three major infectious diseases; HCV, HBV and HIV. Donors represent a healthy population, but several excellent analyses for data on donors present good population estimates, with limitations. One issue however, might be the truncation of the age distribution since there are age limits for donating blood.
If you have a specific group of individuals at risk of infection you might want to focus on these. Extrapolation to national data however, become difficult since the numbers are small. We know that in most places HCV is associated with a high rate of IV drug use. Many of these individuals are also at high risk for HIV.
If a country has a system, like in the US, for reporting HCV and HIV infection that is compulsory and reported for a number of jurisdictions these data can provide estimates of both incidence and prevalence of infections. The US CDC makes their population estimates of HCV based on such reporting systems. It does not cover the whole of the US since reporting does not cover the whole country. But you do get estimates of both incidence and prevalence. Our country's estimates are based on a small case series each year. The data however, are good for assessing trends and demographic relationships, recognizing the limitations of the data.
The data report that Joop referenced clearly illustrates the value of using treatment centers for collecting incidence and prevalence data. Again, though these are gained from people presenting at treatment centers. They estimate that in 2014 there were 18,355 people in the Netherlands living with HIV. I did a quick read and did not see this extrapolated to population rates, but it might be there. In addition there is an excellent reference given for using stochastic simulation models for making population estimates. Whatever system you use to determine prevalence of HCV you will need to make substantial assumptions unless in Spain you have some form of national health survey that actually makes determines of viral infection through analysis of blood samples along with health histories.
Buenas noches Juan. Te estoy enviando un estudio similar al tuyo para que tengas una guía y tomes decisiones.
Objective
To study the prevalence and factors associated with HIV and HCV infection among inmates of a Spanish prison.
Method
A cross-sectional study was carried out in July 2001. We determined HCV (ELISA and RIBA-3) and HIV (ELISA and Western-blot) serology in the prison population. Study variables included age, sex, nationality and previous intravenous drug use (IDU). In IDU inmates we analyzed the age when intravenous drug use was initiated, years of consumption, age at first admission in prison and syringe sharing with other inmates. The subpopulations of Arab and Romani (gypsy) inmates were studied differentially.
Results
A total of 800 inmates (mean age 34.2 ± 6.2 years) were evaluated; 74.3% were Spanish and 33.6% IDU. HCV serology was obtained in 730 inmates and HIV serology in 773 with the following seroprevalence results: HCV 38.2%, HIV 19.1% and HCV-HIV co-infection 18.8%. The variables associated with HCV or HIV infection in the univariate analysis were Spanish nationality, previous IDU and coinfection by the other virus. In the multivariate analysis, only coinfection and, particularly, previous IDU (HCV infection: adjusted ORp 104.8 [95% CI: 49.4-222.2]) (HIV infection adjusted ORp 45.1 [95% CI: 14.0-144.9]) maintained an association with the two infections.
Conclusions
The prevalence of HIV and HCV infection and coinfection is high in Spanish prisons. Infection by either of these viruses and previous IDU were independently associated with both infections. The percentage of non-Spanish inmates with these infections is low.
Correspondencia: Dr. J. Portilla. Unidad de Enfermedades Infecciosas. Hospital General Universitario de Alicante. Maestro Alonso, 109. 03010 Alicante. España.
Copyright © 2005 Elsevier España S.L. All rights reserved.
Thank you all for the feedback.
What we did has been published in Open Forum Infectious Diseases; the new IDSA journal
https://www.researchgate.net/publication/297897944_HIVHCV_coinfection_in_Spain_prevalence_and_patient_characteristics
Article HIV/HCV coinfection in Spain: prevalence and patient characteristics
Two sources of data can be used to measure the burden of any disease like HIV and HCV. Surveillance data particularly of the surveillance system is of high quality in coverage. Alternatively a cross-sectional study would yield prevalence rates and mortality rates also. Burden may encompass also economic aspects on individuals, families and the health care system
In the presence of reliable, high quality data, adopt a combination of retrospective cohort, cross sectional and cohort studies. These will enable you determine prevalence, incidence and trend.
if reliable data is available then cross sectional and retrospective cohort study would be highly beneficial. Although the costs will be high.
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