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Background: Chikungunya is a mosquito-borne disease caused by an arthritogenic alphavirus, with four genotypes: East Central South African (ECSA), West African, ECSA-diverged or Indian Ocean Lineage (IOL) and Asian lineage. Overall, the disease is self-limited; however, in some patients, joint pain and other non-specific symptoms can last for months or years. This systematic review and meta-analysis aims to estimate the proportion of people that self-report chikungunya-related chronic non-specific symptoms., Methods: Medline, EMBASE, Global Health Library and Scopus were searched for articles published before March 2017. Case-control, cohort, cross-sectional, clinical trials studies and outcome-independent case series were eligible. It was estimated that the proportion of patients who did not recover, by virus genotype, and by the time between disease onset and assessment of chronic symptoms., Results: A total of 38 studies were included in the review and 34 in the meta-analysis. Of 6532 chikungunya patients, 3157 did not recover fully after 3 months. The overall no recovery rate associated with chikungunya was 43% (95% CI, 35-52%); Inter-genotype group heterogeneity was observed, the highest prevalence in the ECSA-diverged genotype: 50% (95% CI; 40-60%), followed by the Asian lineage genotype: 36% (95% CI; 20-52%). After 12 months follow-up, the overall no-recovery rate was 21% (95% CI; 19-22%)., Conclusion: The evidence suggests that the prevalence of chronic discomfort associated with chikungunya illness varies by virus lineage. The proportion of people that do not fully recovered after chikungunya was high and, therefore, health authorities must prepare to treat patients with symptoms of long-lasting chikungunya adequately addressing the physical, psychological and social needs.

background Verbal autopsy (VA) is used to ascertain causes of death using information obtained from bereaved relatives. Causes of death can be ascertained from VA questionnaires by a panel of physicians or from predefined algorithms. In a previous study, we developed data-derived algorithms using VA data from 796 adult deaths in hospitals in Tanzania, Ethiopia, and Ghana (primary sites). These computerized algorithms accurately estimated the cause-specific mortality fractions (CSMFs) for deaths due to injuries, meningitis, TB/AIDS and diarrhoeal diseases in the primary sites. Since the same data were used to generate and to validate the algorithms, the accuracy of our algorithms may have been overestimated. We report here on the validity of the algorithms when they were applied to VA data from two secondary sites in Ghana and Tanzania. Here, 'validity' is taken to mean the degree to which the algorithms replicated the physician-generated CSMF for major causes of death, when applied to the same VA data. methods VA interviews were conducted in two secondary sites: in Navrongo, Ghana, on 406 adult deaths, where three local physicians independently reviewed the questionnaires and assigned a cause of death. In Morogoro, Tanzania, VA interviews were conducted on 209 adult deaths, and a panel of physicians independently reviewed the VA questionnaires together with the hospital death certificates or hospital records to determine the cause of death. The CSMF obtained using each algorithm was compared with the CSMF obtained using physician review. results For injuries and meningitis, the algorithms and physician review estimated a similar CSMF in the Morogoro and Navrongo data. For TB/AIDS, the algorithm estimated a similar CSMF as the physicians in Morogoro. The algorithm for diarrhoeal diseases did not agree closely with the physicians in Morogoro or Navrongo. conclusions In general, our data-derived algorithms for assigning causes of death due to injuries, meningitis, and TB/AIDS estimated a similar CSMF as the physicians in the secondary sites. Recommendations for further validation and refinement are discussed. Computerized algorithms offer a potentially quick, affordable, and feasible method for assigning causes of death in mortality surveillance or studies using VA.

Background: Verbal autopsy (VA) has been widely used to ascertain causes of child deaths, but little is known about the usefulness of VA for adult deaths. This paper describes the process used to develop a VA tool for adult deaths and the results of a multicentre validation of this tool., Methods: A mortality classification was developed by including causes of death that might be arrived at by VAs and causes that are responsive to public health interventions. An algorithm was designed for each cause in the classification, based on classifying symptoms into essential, supportive and differential. A structured questionnaire designed to elicit information on these symptoms was developed in English translated into the local languages. The tool was validated on deaths occurring at hospitals in Tanzania (315 deaths), Ethiopia (249) and Ghana (232). Hospital records of all adult deaths occurring at the study hospitals from June 1993 to April 1995 were collected prospectively. Non-medical interviewers with at least 12 years of formal education conducted VA interviews. Causes of death were diagnosed by a panel of physicians and by a computerized algorithm. The validity of the VA was assessed by comparing the VA diagnoses with hospital diagnoses., Results: Specificity of VAs by physicians fell below 95% only for acute febrile illness (AFI) and TB/AIDS. Sensitivity and positive predictive value (PPV), however, varied widely both across the sites and between causes. Sensitivity was > 75% for tetanus, rabies, direct maternal causes, injuries and TB/AIDS and ranged between 60% and 74% for diarrhoea, acute abdominal conditions and AFI. The PPV was > 75% for tetanus, rabies, hepatitis and injuries and ranged between 60 and 74% for meningitis, AFI, TB/AIDS and direct maternal causes. When the communicable diseases were combined in a single group, the sensitivity was 82%, specificity 78% and PPV 85%. For the group of noncommunicable diseases the corresponding sensitivity, specificity and PPV were 71%, 87% and 67%, respectively. Use of an algorithm resulted in lower sensitivity, specificity and PPV than the VAs by physician., Conclusion: VAs by a panel of physicians performed better than an opinion-based algorithm. The validity of VA diagnosis was highest for AFI, direct maternal causes, TB/AIDS, tetanus, rabies and injuries.