Posts tagged “epi”

Introducing HAPIT

I’ve lead recent efforts to create a web-based tool to estimate the impacts of household air pollution interventions (like stoves, gas dissemination, etc) using methods based on what’s known about household air pollution and its contribution to the Global Burden of Disease. The project began as an Excel-based spreadsheet before moving to the web leveraging Shiny, R, and a fair amount of javascript. From the site:

HAPIT estimates and compares health benefits attributable to stove and/or fuel programs that reduce exposure to household air pollution (HAP) resulting from solid fuel use in traditional stoves in developing countries. HAPIT allows users to customize two scenarios based on locally gathered information relevant to their intervention, which is the recommended approach. This will normally require preliminary field work at the dissemination site to demonstrate pollution exposures before and after the intervention in a representative sample of households. If no local information is available, however, HAPIT contains conservative default values for four broad classes of household energy interventions based on the available literature — liquid fuels, chimney stoves, rocket stoves, and advanced combustion stoves. As each country’s health and HAP situation is different, HAPIT currently contains the background data necessary to conduct the analysis in 55 countries — those with more than 50% of households using solid fuels for cooking and China, which has a lower percentage of households using solid fuels for cooking, but a high number in absolute terms. See the drop down list on the left and the Info tab for more details.

HAPIT also estimates program cost-effectiveness in US dollars per averted DALY (disability-adjusted life year) based on the World Health Organization’s CHOICE methodology (see Info tab for more detail). It takes a financial accounting approach in that it 1) does not take into account the household costs such as fuel and health expenses or time spent cooking or acquiring fuel and 2) assumes that programs are covering the cost of fuel-based interventions (such as annual LPG costs per household). For custom scenarios, users can adjust the per-household maintenance or fuel cost based on the characteristics of their programs. All program costs should be entered in current US dollars.

There are a number of nice features of HAPIT, but one I’m particularly fond of is the customized, session-based pdf generated by clicking “Download Report.” HAPIT’s a work in progress and will continue to evolve in the coming months.

Council on Foreign Relations: Vaccine Preventable Disease Map

It’s been a long time, blog. Blame India and Nepal. Both of which are seemingly under-represented in the below map. View the map in your full browser window here; I had to yank the embedded code because it was causing all kinds of issues.

For the past three years, the Global Health program at the Council on Foreign Relations has been tracking relevant reports to produce an interactive map plotting global outbreaks of diseases that are easily prevented by inexpensive and effective vaccines. The diseases include measles, mumps, whooping cough, polio, and rubella.

“These outbreaks illustrate a worrying trend and raise the sense of alarm regarding failures in and public resistance to vaccine efforts,” says CFR senior fellow for global health Laurie Garrett. “Small decreases in vaccine coverage are known to lead to dramatic increases in outbreaks of vaccine-preventable diseases,” she explains.

R + Global Burden of Disease / Comparative Risk Assessment Data: A tutorial (version 0.1)

R can be scary for those new to it, but it is exceptionally useful for a number of things, including managing, importing, and merging text files; resaving them; and performing statistical analyses to your heart’s content. It is your friend, albeit one that you must learn to love slowly and painfully.

This brief tutorial does not serve as an introduction to R. Instead, it focuses on reading in a large, complex data set with ~1 million rows and 50+ columns. It was created to help facilitate some analysis in a GBD course at Berkeley. It will help you figure out how to do some basic manipulation and subsetting and export these subsetted data into a comma-separated text file (“csv”) for analysis in your favorite spreadsheet program. It is a work in progress and will be updated over time.

Queue head explosion

… the effect of JSY on health-system outputs and outcomes using district-level differences in differences that controlled for differences between treated and untreated observations, and differences in treated observations that might have resulted from underlying changes over time…

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