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Three charts that explain AIDS in 2015

Tariq Khokhar's picture

Today is World Aids Day - an annual event to raise awareness about the global fight against HIV. Earlier this year, a report from UNAIDS declared that the Millennium Development Goal 6 target of “halting and reversing the spread of HIV” had been met, but that continued effort and financing would be needed to end the AIDS epidemic by 2030 as part of Sustainable Development Goal 3.

When it comes to international data about HIV and AIDS, the cross-organisational UNAIDS program publishes age and gender-disaggregated data on indicators such as prevalence, new infections and deaths. In turn, we incorporate some of these data into the World Development Indicators.

Here are some highlights from the most recently available data:

Globally, 37 million adults and children live with HIV


In 2014, there were an estimated 36.9 million adults and children living with HIV in the world. The majority of these people are in Sub-Saharan Africa and parts of Asia. As you can see from the decreasing slope of the “global” line - while people continue to become infected, the rate of new infections is going down.
 

Data Lab Link Roundup: Analysing taxis, Ubers and bikes, the Economist on open data, simple explanations, digital archives, optimistic statisticians, plot.ly, and lying with the y-axis

Tariq Khokhar's picture


Here are some (of the many) things that caught our attention last week:

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Where are there laws against domestic violence?

Tariq Khokhar's picture

Globally, the most common form of violence women experience is from an intimate partner. A recent report found that 127 out of 173 economies studied had laws on domestic violence, and in 72% of economies, protection orders can be used to limit an abuser's behavior. Read more.

 

Are we ready to embrace big private-sector data?

Andrew Whitby's picture



The use of big data to help understand the global economy continues to build momentum. Last week our sister institution, the International Monetary Fund, launched their own program in big data, with a slate of interesting speakers including Hal Varian (Google Chief Economist), Susan Athey (Professor at Stanford GSB and a former Microsoft Chief Economist) and DJ Patil (Chief Data Scientist of the United States).
 
The day's speakers grappled with the implications of big data for the Fund's bread-and-butter macroeconomic analysis--a topic of great interest to the World Bank Group too. Examples were presented in which big data is used to generate macroeconomic series that have traditionally been the preserve of national statistical offices (NSOs): for example, MIT's Billion Prices Project, which measures price inflation in a radically different way from traditional CPI statistics.
 

Should we continue to use the term “developing world”?

Tariq Khokhar's picture
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Comparing the classification of countries.

Humans, by their nature, categorize. Economists are no different. For many years, the World Bank has produced and used income classifications to group countries.  

The low, lower-middle, upper-middle and high income groups are each associated with an annually updated threshold level of Gross National Income (GNI) per-capita, and the low and middle income groups taken together are referred to in the World Bank (and elsewhere) as the “developing world.

This term is used in our publications (such as the World Development Indicators and the Global Monitoring Report) and we also publish aggregate estimates for important indicators like poverty rates for both developing countries as a group and for the whole world.

But the terms “developing world” and “developing country” are tricky: even we use them cautiously, trying to make it clear that we're not judging the development status of any country.

Income growth in Latin America has stopped being pro-poor during the slowdown

Oscar Calvo-González's picture

The team behind the World Bank’s LAC Equity Lab is starting this new blog series to showcase our favorite charts and visuals that help tell the story of recent developments in poverty and equity in Latin America and the Caribbean. We welcome your comments and ideas, and invite you to explore our LAC Equity Lab and World Bank Poverty websites to learn more.
 
In this first installment, we are tackling a pressing issue for the region – income growth and its implications on inequality.
 
Income growth in Latin America has stopped being pro-poor during the slowdown
 

Source: SEDLAC (World Bank and CEDLAS). Note: growth incidence curves (GIC) show the annualized growth rate of income for every percentile of the income distribution and are calculated using pooled harmonized data from 17 countries. In order to analyze the same set of countries every year, interpolation was applied when country data were not available for a given year.

Climate change's biggest effect on poverty? Agriculture.

Tariq Khokhar's picture

The biggest impact climate change will have on the poor will be through agriculture. Under a pessimistic "poverty" scenario with high climate change impacts, there could be more than 100 million additional people in poverty by 2030, largely due to changing crop yields and prices. Under an optimistic "prosperity" scenario, these effects are greatly reduced. Read more in the new "Shock Waves" report.

 

How we made #OpenIndia

Ankur N's picture

Cross posted from the End Poverty in South Asia blog

open india

It has been a season ripe with new ideas and shifts in the open data conversation. At the Cartagena Data Festival in April, the call for a country-led data revolution was loud and clear. Later in June at the 3rd International Open Data Conference in Ottawa there was an emphasis on the use of open data-beyond mere publishing.

Mulling on these takeaways, a logical question to ask may be: what would a country-focused data project that aims to put data to use look like?

How long does it take to start a business in your country?

Tariq Khokhar's picture
One of the most interesting trends in Doing Business is the reduction in the number of days it takes to start a business across the world. Navigate through the graphic below using the arrows next to the captions and then select any countries or groupings you'd like to see with the dropdown menu at the bottom.
 
 

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