Reduced burden of childhood diarrheal diseases through increased access to water and sanitation in India : a modeling analysis

Each year, more than 300,000 children in India under the age of five years die from diarrheal diseases. Clean piped water and improved sanitation are known to be effective in reducing the mortality and morbidity burden of diarrhea but are not yet available to close to half of the Indian population. In this paper, we estimate the health benefits (reduced cases of diarrheal incidence and deaths averted) and economic benefits (measured by out-of-pocket treatment expenditure averted and value of insurance gained) of scaling up the coverage of piped water and improved sanitation among Indian households to a near-universal 95% level. We use IndiaSim, a previously validated, agent-based microsimulation platform to model disease progression and individual demographic and healthcare-seeking behavior in India, and use an iterative, stochastic procedure to simulate health and economic outcomes over time. We find that scaling up access to piped water and improved sanitation could avert 43,352 (95% uncertainty range [UR] 42,201-44,504) diarrheal episodes and 68 (95% UR 62-74) diarrheal deaths per 100,000 under-5 children per year, compared with the baseline. We estimate a saving of (in 2013 US$)$357,788 (95% $345,509-$370,067) in out-of-pocket diarrhea treatment expenditure, and $1646 (95$1603-$1689) in incremental value of insurance per 100,000 under-5 children per year over baseline. The health and financial benefits are highly progressive, i.e. they reach poorer households more. Thus, scaling up access to piped water and improved sanitation can lead to large and equitable reductions in the burden of childhood diarrheal diseases in India

The Socioeconomic and Institutional Determinants of Participation in India's Health Insurance Scheme for the Poor.

The Rashtriya Swasthya Bima Yojana (RSBY), which was introduced in 2008 in India, is a social health insurance scheme that aims to improve healthcare access and provide financial risk protection to the poor. In this study, we analyse the determinants of participation and enrolment in the scheme at the level of districts. We used official data on RSBY enrolment, socioeconomic data from the District Level Household Survey 2007-2008, and additional state-level information on fiscal health, political affiliation, and quality of governance. Results from multivariate probit and OLS analyses suggest that political and institutional factors are among the strongest determinants explaining the variation in participation and enrolment in RSBY. In particular, districts in state governments that are politically affiliated with the opposition or neutral parties at the centre are more likely to participate in RSBY, and have higher levels of enrolment. Districts in states with a lower quality of governance, a pre-existing state-level health insurance scheme, or with a lower level of fiscal deficit as compared to GDP, are significantly less likely to participate, or have lower enrolment rates. Among socioeconomic factors, we find some evidence of weak or imprecise targeting. Districts with a higher share of socioeconomically backward castes are less likely to participate, and their enrolment rates are also lower. Finally, districts with more non-poor households may be more likely to participate, although with lower enrolment rates

Hypersonic vitrectomy in intraoperative posterior capsular rupture with retained nuclear fragments

In our report, we present the hypersonic vitrectomy (Vitesse, Bausch and Lomb) being employed for anterior vitreous liquefaction and removal in posterior capsular rupture. The capsular tear with nucleus drop during conventional phacoemulsification was managed by vitrectomy using the hypersonic vitrector after posterior-assisted levitation followed by intraocular lens (IOL) implantation. The minimal cortical and epinuclear lens particles in the anterior chamber and vitreous were also liquefied with a stoke length of 30 to 40 μm and aspirated via the Vitesse vitrectomy system. The same probe performs the vitrectomy and the nucleus removal. The postoperative period was uneventful with clear cornea, normal fundus, and 20/20 best-corrected visual acuity (BCVA). The hypersonic vitrectomy utilizes the ultrasound power of 29.5 kHz and a stoke length of 0 to 60 μm for liquefaction of the vitreous. It can be a safe alternative for vitrectomy and lens removal in a single setting

RSBY Participation and Enrolment rate regression estimates.

<p>Source: RSBY website (<a href="http://www.rsby.gov.in" target="_blank">www.rsby.gov.in</a>) for enrolment data, downloaded on 22 May 2012. DLHS 2007–2008 for socioeconomic data, RBI (2013) for state fiscal data, and corruption index is from CII-TMS (2007). Coefficients that are statistically significant at 10%, 5%, and 1% level are marked with *, **, and *** respectively. Huber-White robust standard errors are used in all regressions.</p

Number of RSBY participating districts by state.

<p>Source: <a href="http://rsby.gov.in/" target="_blank">http://rsby.gov.in/</a>, data downloaded on 22 May 2012. Note: Total no. of districts in states reflect those surveyed in DLHS 2007–08. Since the survey, additional districts have been created, but are not mentioned in this table. Districts in Nagaland have not been included since no DLHS data are available for the state.</p

State level political and corruption classifications.

<p><b>Source:</b> Political affiliation data compiled from various sources. Corruption Index is from TII-CMS 2007. Affiliation index coded as 0 = BJP (principal opposition party at centre); 1 = National Democratic Alliance (NDA) coalition partner; 2 = Indian National Congress (INC) is principal opposition party/UPA coalition partner is principal opposition party, at state; 3 = Neutral party; 4 = UPA coalition partner; 5 = ruling party at centre, INC.</p

Descriptive Statistics- Means, Standard deviations and number of observations for model variables.

*<p>Average no. of schemes implemented assesses the implementation of all schemes surveyed in DLHS 2007–08 at the village level.</p>**<p>Enrolment time measures the number of days between commencement of enrolment in district and May 22, 2012.</p>†<p>Any political change since 2008 is a binary variable capturing any change in ruling party since 2008.</p>††<p>Degree of political shift is an interaction term capturing swing in political affiliation (based on affiliation index) given political change since 2008.</p>***<p>Data sources: District level data from DLHS 2007–08, Enrolment rate information from <a href="http://www.rsby.gov.in" target="_blank">http://www.rsby.gov.in</a>, State fiscal data from Reserve Bank of India (2013)- State Finances A Study of Budgets of 2012–13 and Corruption index constructed from TII-CMS 2007 survey.</p