Vemu Lakshmi

An epidemic of Chikungunya fever of unprecedented magnitude occurred in many parts of India in early 2006 after an interval of 33 years, and there has been a resurgence in some parts of South India since June 2007. The article highlights clinical manifestations of infection and various molecular tests that were used for diagnoses of Chikungunya virus infection. Of particular interest is the real-time loop-mediated isothermal amplification (RT LAMP) assay, which is rapid and cost-effective and can be adopted at ill-equipped laboratories. Clinical symptoms were characterized by a triad of fever, rash, and severe rheumatic manifestations. RT LAMP identified 20 additional Chikungunya virus-positive cases, compared with reverse-transcriptase polymerase chain reaction. Chikungunya virus was isolated from 20 randomly selected samples. Genotyping of the virus isolates revealed that the East Central South African genotype of Chikungunya virus was the etiologic agent of this epidemic. Molecular diagnosis is an important tool to identify such new vectorborne viral illnesses.

The HIV burden estimate for India has a very wide plausibility range. A recent population-based study in a south Indian district demonstrated that the official method used in India to estimate HIV burden in the population, which directly extrapolates annual sentinel surveillance data from large public sector antenatal and sexually transmitted infection (STI) clinics, led to a 2–3 times higher estimate than that based on population-based data. We assessed the generalisability of the reasons found in the Guntur study for overestimation of HIV by the official sentinel surveillance based method: addition of substantial unnecessary HIV estimates from STI clinics, the common practice of referral of HIV positive/suspect patients by private practitioners to public hospitals, and a preferential use of public hospitals by lower socioeconomic strata. We derived conservative correction factors for the sentinel surveillance data and titrated these to the four major HIV states in India (Andhra Pradesh, Maharashtra, Karnataka and Tamil Nadu), and examined the impact on the overall HIV estimate for India. HIV data from STI clinics are not used elsewhere in the world as a component of HIV burden estimation in generalised epidemics, and the Guntur study verified that this was unnecessary. The referral of HIV positive/suspect patients from the private to the public sector is a widespread phenomenon in India, which is likely causing an upward distortion in HIV estimates from sentinel surveillance in other parts of India as well. Analysis of data from the nationwide Reproductive and Child Health Survey revealed that lower socioeconomic strata were over-represented among women seeking antenatal care at public hospitals in all major south Indian states, similar to the trend seen in the Guntur study. Application of conservative correction factors derived from the Guntur study reduced the 2005 official sentinel surveillance based HIV estimate of 3.7 million 15–49 years old persons in the four major states to 1.5–2.0 million, which would drop the official total estimate of 5.2 million 15–49 years old persons with HIV in India to 3–3.5 million. Plausible and cautious extrapolation of the trends seen in a recent large and rigorous population-based study of HIV in a south Indian district suggests that India is likely grossly overestimating its HIV burden with the current official sentinel surveillance based method. This method needs revision.

The human immunodeficiency virus (HIV) burden among adults in India is estimated officially by direct extrapolation of annual sentinel surveillance data from public-sector antenatal and sexually transmitted infection (STI) clinics and some high-risk groups. The validity of these extrapolations has not been systematically examined with a large sample population-based study. We sampled 13838 people, 15–49 years old, from 66 rural and urban clusters using a stratified random method to represent adults in Guntur district in the south Indian state of Andhra Pradesh. We interviewed the sampled participants and obtained dried blood spots from them, and tested blood for HIV antibody, antigen and nucleic acid. We calculated the number of people with HIV in Guntur district based on these data, compared it with the estimate using the sentinel surveillance data and method, and analysed health services use data to understand the differences. In total, 12617 people (91.2% of the sampled group) gave a blood sample. Adjusted HIV prevalence was 1.72% (95% confidence interval 1.35–2.09%); men 1.74% (1.27–2.21%), women 1.70% (1.36–2.04%); rural 1.64% (1.10–2.18%), urban 1.89% (1.39–2.39%). HIV prevalence was 2.58% and 1.20% in people in the lower and upper halves of a standard of living index (SLI). Of women who had become pregnant during the past 2 years, 21.1% had used antenatal care in large public-sector hospitals participating in sentinel surveillance. There was an over-representation of the lowest SLI quartile (44.7%) in this group, and 3.61% HIV prevalence versus 1.08% in the remaining pregnant women. HIV prevalence was higher in that group even when women were matched for the same SLI half (lower half 4.39%, upper 2.63%) than in the latter (lower 1.06%, upper 1.05%), due to referral of HIV-positive/suspected women by private practitioners to public hospitals. The sentinel surveillance method (HIV prevalence: antenatal clinic 3%, STI clinic 22.8%, female sex workers 12.8%) led to an estimate of 112635 (4.38%) people with HIV, 15–49 years old, in Guntur district, which was 2.5 times the 45942 (1.79%) estimate based on our population-based study. The official method in India leads to a gross overestimation of the HIV burden in this district due to addition of substantial extra HIV estimates from STI clinics, the common practice of referral of HIV-positive/suspected people to public hospitals, and a preferential use of public hospitals by people in lower socioeconomic strata. India may be overestimating its HIV burden with the currently used official estimation method.