Leaving no one behind: a methodology for setting health inequality reduction targets for Sustainable Development Goal 3.

Objectives: To present a methodology for the simultaneous setting of quantitative targets that reflect both an improvement in the national average of an indicator for Sustainable Development Goal 3 (SDG3), as well as a reduction in its geographic inequality.

Methods: A five-step algorithm was developed: (a) calculate the national average annual percent change (AAPC) for an SDG3 indicator; (b) normatively define geographic strata from the subnational distribution of the indicator in a baseline year; (c) apply a proportional progressivity criterion to the AAPC to project the stratum-specific indicator value for the target year; (d) set the national target as the weighted average of the indicator in the subnational territorial units for the target year; and (e) set the inequality reduction targets by calculating the absolute and relative gaps between the bottom and top strata for the target year.

Results: The algorithm was applied to SDG indicator 3.

[Leaving no one behind: Methodology to set health inequality reduction targets for Sustainable Development Goal 3Não deixar ninguém para trás: uma metodologia para estabelecer metas de redução das desigualdades em saúde sob o Objetivo de Desenvolvimento Sustentável 3].

Objectives: Present methodology for the concurrent development of quantitative targets that reflect improvement in the national average of an indicator for Sustainable Development Goal 3 (SDG3), as well as a reduction in geographic inequality.

Methods: A five-step algorithm was developed: a) calculate the national average annual percentage change (AAPC) for an SDG3 indicator; b) standardize the definition of geographic strata based on subnational distribution of the indicator in a base year; c) apply a criterion for proportional progress in the AAPC in order to project the stratum-specific indicator to the target year; d) set the national target as the weighted average of the indicator in the subnational territorial units for the target year; and e) develop inequality reduction targets by calculating absolute and relative gaps between the top and bottom strata for the target year.

Results: The algorithm was applied to SDG indicator 3.

Risk of dengue for tourists and teams during the World Cup 2014 in Brazil.

Background: This year, Brazil will host about 600,000 foreign visitors during the 2014 FIFA World Cup. The concern of possible dengue transmission during this event has been raised given the high transmission rates reported in the past by this country.

Methodology/principal Findings: We used dengue incidence rates reported by each host city during previous years (2001-2013) to estimate the risk of dengue during the World Cup for tourists and teams.