Prevalence of Hepatitis C Virus in Brazil's Inmate Population: A Systematic Review

OBJECTIVE

To estimate the prevalence of hepatitis C virus infection in Brazil's inmate population.

METHODS

Systematic review on hepatitis C virus infection in the inmate population. Brazilian studies published from January 1, 1989 to February 20, 2014 were evaluated. The methodological quality of the studies was assessed using a scale of 0 to 8 points.

RESULTS

Eleven eligible studies were analyzed and provided data on hepatitis C virus infection among 4,375 inmates from seven states of Brazil, with a mean quality classification of 7.4. The overall hepatitis C virus prevalence among Brazilian inmates was 13.6% (ranging from 1.0% to 41.0%, depending on the study). The chances of inmates being seropositive for hepatitis C virus in the states of Minas Gerais (MG), Sergipe (SE), Mato Grosso do Sul (MS), Rio Grande do Sul (RS), Goiás (GO) and Espirito Santo (ES) were 84.0% (95%CI 0.06;0.45), 92.0% (95%CI 0.04;0.13), 88.0% (95%CI 0.09;0.18), 74.0% (95%CI 0.16;0.42), 84.0% (95%CI 0.08;0.31) and 89.0% (95%CI 0.01;0.05) respectively, lower than that observed in the Sao Paulo state (seroprevalence of 29.3%). The four studies conducted in the city of Sao Paulo revealed a lower prevalence in more recent studies compared to older ones.

CONCLUSIONS

The highest prevalence of hepatitis C virus infection in Brazil's inmate population was found in Sao Paulo, which may reflect the urban diversity of the country. Despite Brazilian studies having good methodological quality to evaluate the prevalence of the hepatitis C virus, they are scarce and lack data on risk factors associated with this infection, which could support decisions on prevention and implementation of public health policies for Brazilian prisons.

Prevalence of hepatitis C virus among inmate populations grouped into seven different states of Brazil.

State	Positive samples	Sample size	HCV sero-prevalence (%)	95%CI		OR	95%CI		p
				Lower	Upper		Lower	Upper
Sao Paulo	624	2,131	29.3	27.3	31.2	Ref.	–	–	< 0.001
Minas Gerais	4	63	6.3	0.3	12.4	0.16	0.06	0.45
Sergipe	13	422	3.1	1.4	4.7	0.08	0.04	0.13
Mato Grosso do Sul	33	686	4.8	3.2	6.4	0.12	0.09	0.18
Rio Grande do Sul	19	195	9.7	5.6	13.9	0.26	0.16	0.42
Goias	9	148	6.1	2.2	9.9	0.16	0.08	0.31
Espirito Santo	7	730	1.0	0.3	1.7	0.02	0.01	0.05
Total	709	4,375	16.2	15.1	17.3	–	–	–

Full article at:   http://goo.gl/tgGDws

By:  Magri MC1, Ibrahim KY2, Pinto WP2, França FO2, Bernardo WM3, Tengan FM2.

• 1Laboratório de Investigação Médica em Hepatologia por Vírus, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brasil.
• 2Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brasil.
• 3Centro de Desenvolvimento de Educação Médica, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brasil. 
• Rev Saude Publica. 2015;49:36. doi: 10.1590/S0034-8910.2015049005886. Epub 2015 Jul 31.

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Genetic Diversity and Molecular Epidemiology of Multidrug-Resistant Mycobacterium Tuberculosis in Minas Gerais State, Brazil

Below:  Minimum Spanning Tree (MST) obtained from the spoligotyping dataset (n = 104 MDR-TB isolates) identified from 2008 to 2013 in Minas Gerais, Brazil. Color code indicates major subclades found within the Lineage 4 (Euro-American), LAM, T, H, X, S and U

Fifty-seven different IS6110-RFLP patterns were found, among which 50 had unique patterns and 17 were grouped into seven clusters. The discriminatory index (Hunter and Gaston, HGDI) for RFLP was 0.9937. Ninety-nine different MIRU-VNTR patterns were found, 95 of which had unique patterns and nine isolates were grouped into four clusters. The major allelic diversity index in the MIRU-VNTR loci ranged from 0.6568 to 0.7789. The global HGDI for MIRU-VNTR was 0.9991. Thirty-two different spoligotyping profiles were found: 16 unique patterns (n = 16) and 16 clustered profiles (n = 88). The HGDI for spoligotyping was 0.9009. The spoligotyped clinical isolates were phylogenetically classified into Latin-American Mediterranean (66.34 %), T (14.42 %), Haarlem (5.76 %), X (1.92 %), S (1.92 %) and U (unknown profile; 8.65 %). Among the U isolates, 77.8 % were classified further by 3R-SNP-typing as 44.5 % Haarlem and 33.3 % LAM, while the 22.2 % remaining were not classified. Among the 104 clinical isolates, 86 were identified by TB-SPRINT as MDR, 12 were resistant to rifampicin only, one was resistant to isoniazid only, three were susceptible to both drugs, and two were not successfully amplified by PCR. A total of 42, 28 and eight isolates had mutations in rpoB positions 531, 526 and 516, respectively. Correlating the cluster analysis with the patient data did not suggest recent transmission of MDR-TB.

Although our results do not suggest strong transmission of MDR-TB in Minas Gerais (using a classical 100 % MDR-TB identical isolates cluster definition), use of a smoother cluster definition (>85 % similarity) does not allow us to fully eliminate this possibility; hence, around 20–30 % of the isolates we analyzed might be MDR-TB transmission cases.

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