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Beyond crystal balls: crosscutting solutions in global health to prepare for an unpredictable future.

Alonso WJ, McCormick BJ, Miller MA, Schuck-Paim C, Asrar GR - BMC Public Health (2015)

Bottom Line: Predictive modeling is frequently used to assist planning, but outcomes depend heavily on a subset of critical assumptions, which are mostly hampered by our limited knowledge about the many factors, mechanisms and relationships that determine the dynamics of disease systems, by a lack of data to parameterize and validate models, and by uncertainties about future scenarios.This system should be able to reveal crosscutting solutions with the potential to address not only one threat, but multiple areas of vulnerability to future health risks.Actionable knowledge not based on a narrow subset of threats and conditions can better guide policy, build societal resilience and ensure effective prevention in an uncertain world.

View Article: PubMed Central - PubMed

Affiliation: Fogarty International Center, National Institutes of Health, Bethesda, Maryland, 20892, USA. alonsow@mail.nih.gov.

ABSTRACT

Background: Efforts in global heath need to deal not only with current challenges, but also to anticipate new scenarios, which sometimes unfold at lightning speed. Predictive modeling is frequently used to assist planning, but outcomes depend heavily on a subset of critical assumptions, which are mostly hampered by our limited knowledge about the many factors, mechanisms and relationships that determine the dynamics of disease systems, by a lack of data to parameterize and validate models, and by uncertainties about future scenarios.

Discussion: We propose a shift from a focus on the prediction of individual disease patterns to the identification and mitigation of broader fragilities in public health systems. Modeling capabilities should be used to perform "stress tests" on how interrelated fragilities respond when faced with a range of possible or plausible threats of different nature and intensity. This system should be able to reveal crosscutting solutions with the potential to address not only one threat, but multiple areas of vulnerability to future health risks. Actionable knowledge not based on a narrow subset of threats and conditions can better guide policy, build societal resilience and ensure effective prevention in an uncertain world.

No MeSH data available.


Related in: MedlinePlus

The “F-diagram” clustering routes of transmission for diarrheal pathogens [72]. WASH (water, sanitation and hygiene) programs attempt to tackle the common routes of infection rather than separately address individual pathogens
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Fig2: The “F-diagram” clustering routes of transmission for diarrheal pathogens [72]. WASH (water, sanitation and hygiene) programs attempt to tackle the common routes of infection rather than separately address individual pathogens

Mentions: An excellent example of a health fragility is illustrated by the Mills-Reincke phenomenon [61]. In the 1900s, improvements to municipal water supplies successfully reduced the burden of mortality from typhoid disease – the motivating target for the action. However, all-cause mortality was also reduced (saving between 1.5 to 16 times the number of lives from combined ‘all cause’ compared to the number saved from typhoid alone), as was substantial indirect morbidity with more recent estimates that around 4 % of all deaths might be directly attributable to water/sanitation [62]. At the time the routes of infection and breadth of individual pathogens were unknown, but the same logic is widely applied in WASH (water, sanitation and hygiene) programs that attempt to block routes of infection (Fig. 2) rather than attempt to focus on individual pathogens – of which there are many [63]. WASH programs not only tackle fragilities to multiple enteric infections, but they focus on proximate stressors (e.g. water quality at the point of use, or household hygiene) rather than ultimate stressors that might, for example damage the supply of clean water.Fig. 2


Beyond crystal balls: crosscutting solutions in global health to prepare for an unpredictable future.

Alonso WJ, McCormick BJ, Miller MA, Schuck-Paim C, Asrar GR - BMC Public Health (2015)

The “F-diagram” clustering routes of transmission for diarrheal pathogens [72]. WASH (water, sanitation and hygiene) programs attempt to tackle the common routes of infection rather than separately address individual pathogens
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4581487&req=5

Fig2: The “F-diagram” clustering routes of transmission for diarrheal pathogens [72]. WASH (water, sanitation and hygiene) programs attempt to tackle the common routes of infection rather than separately address individual pathogens
Mentions: An excellent example of a health fragility is illustrated by the Mills-Reincke phenomenon [61]. In the 1900s, improvements to municipal water supplies successfully reduced the burden of mortality from typhoid disease – the motivating target for the action. However, all-cause mortality was also reduced (saving between 1.5 to 16 times the number of lives from combined ‘all cause’ compared to the number saved from typhoid alone), as was substantial indirect morbidity with more recent estimates that around 4 % of all deaths might be directly attributable to water/sanitation [62]. At the time the routes of infection and breadth of individual pathogens were unknown, but the same logic is widely applied in WASH (water, sanitation and hygiene) programs that attempt to block routes of infection (Fig. 2) rather than attempt to focus on individual pathogens – of which there are many [63]. WASH programs not only tackle fragilities to multiple enteric infections, but they focus on proximate stressors (e.g. water quality at the point of use, or household hygiene) rather than ultimate stressors that might, for example damage the supply of clean water.Fig. 2

Bottom Line: Predictive modeling is frequently used to assist planning, but outcomes depend heavily on a subset of critical assumptions, which are mostly hampered by our limited knowledge about the many factors, mechanisms and relationships that determine the dynamics of disease systems, by a lack of data to parameterize and validate models, and by uncertainties about future scenarios.This system should be able to reveal crosscutting solutions with the potential to address not only one threat, but multiple areas of vulnerability to future health risks.Actionable knowledge not based on a narrow subset of threats and conditions can better guide policy, build societal resilience and ensure effective prevention in an uncertain world.

View Article: PubMed Central - PubMed

Affiliation: Fogarty International Center, National Institutes of Health, Bethesda, Maryland, 20892, USA. alonsow@mail.nih.gov.

ABSTRACT

Background: Efforts in global heath need to deal not only with current challenges, but also to anticipate new scenarios, which sometimes unfold at lightning speed. Predictive modeling is frequently used to assist planning, but outcomes depend heavily on a subset of critical assumptions, which are mostly hampered by our limited knowledge about the many factors, mechanisms and relationships that determine the dynamics of disease systems, by a lack of data to parameterize and validate models, and by uncertainties about future scenarios.

Discussion: We propose a shift from a focus on the prediction of individual disease patterns to the identification and mitigation of broader fragilities in public health systems. Modeling capabilities should be used to perform "stress tests" on how interrelated fragilities respond when faced with a range of possible or plausible threats of different nature and intensity. This system should be able to reveal crosscutting solutions with the potential to address not only one threat, but multiple areas of vulnerability to future health risks. Actionable knowledge not based on a narrow subset of threats and conditions can better guide policy, build societal resilience and ensure effective prevention in an uncertain world.

No MeSH data available.


Related in: MedlinePlus