World Solve

Future progress on human development and planetary health depends on solving girls missing school during periods. Conventional approaches have proven insufficient. The required intervention must integrate community knowledge, data and appropriate technology while remaining affordable, privacy-preserving and operable with minimal external support. Strong solutions will articulate measurable impact metrics, risk mitigation strategies, and a plan for sustained operation by local actors after the pilot phase.

Addressing hygiene facilities at school remaining poor is critical for achieving the 2030 Agenda. Current efforts fall short in scale, speed and equity, leaving the most vulnerable behind. Any viable solution must function in low-resource settings with limited specialists, transport, laboratory capacity and broadband. Proposals should specify quantifiable biological, social or environmental outcomes, openly discuss potential risks, and present a realistic pathway for long-term maintenance and local ownership beyond short research pilots.

Future progress on human development and planetary health depends on solving counselling in schools remaining rare. Conventional approaches have proven insufficient. The required intervention must integrate community knowledge, data and appropriate technology while remaining affordable, privacy-preserving and operable with minimal external support. Strong solutions will articulate measurable impact metrics, risk mitigation strategies, and a plan for sustained operation by local actors after the pilot phase.

The problem of school start times remaining too early continues to affect hundreds of millions of people and undermines progress on multiple Sustainable Development Goals. Existing responses remain fragmented, under-resourced and poorly adapted to local contexts. A strong solution must operate effectively under severe constraints of skilled personnel, infrastructure, electricity and connectivity. It should define clear measurable outcomes, identify possible unintended harms, and demonstrate how the intervention can be sustained by local institutions long after initial funding ends.

The problem of school meals remaining unhealthy continues to affect hundreds of millions of people and undermines progress on multiple Sustainable Development Goals. Existing responses remain fragmented, under-resourced and poorly adapted to local contexts. A strong solution must operate effectively under severe constraints of skilled personnel, infrastructure, electricity and connectivity. It should define clear measurable outcomes, identify possible unintended harms, and demonstrate how the intervention can be sustained by local institutions long after initial funding ends.

The problem of gender segregation in school sports continues to affect hundreds of millions of people and undermines progress on multiple Sustainable Development Goals. Existing responses remain fragmented, under-resourced and poorly adapted to local contexts. A strong solution must operate effectively under severe constraints of skilled personnel, infrastructure, electricity and connectivity. It should define clear measurable outcomes, identify possible unintended harms, and demonstrate how the intervention can be sustained by local institutions long after initial funding ends.

The problem of high rates of early school leaving continues to affect hundreds of millions of people and undermines progress on multiple Sustainable Development Goals. Existing responses remain fragmented, under-resourced and poorly adapted to local contexts. A strong solution must operate effectively under severe constraints of skilled personnel, infrastructure, electricity and connectivity. It should define clear measurable outcomes, identify possible unintended harms, and demonstrate how the intervention can be sustained by local institutions long after initial funding ends.

Addressing absent or unreliable internet in rural schools is critical for achieving the 2030 Agenda. Current efforts fall short in scale, speed and equity, leaving the most vulnerable behind. Any viable solution must function in low-resource settings with limited specialists, transport, laboratory capacity and broadband. Proposals should specify quantifiable biological, social or environmental outcomes, openly discuss potential risks, and present a realistic pathway for long-term maintenance and local ownership beyond short research pilots.

The problem of schools unprepared for children with special needs continues to affect hundreds of millions of people and undermines progress on multiple Sustainable Development Goals. Existing responses remain fragmented, under-resourced and poorly adapted to local contexts. A strong solution must operate effectively under severe constraints of skilled personnel, infrastructure, electricity and connectivity. It should define clear measurable outcomes, identify possible unintended harms, and demonstrate how the intervention can be sustained by local institutions long after initial funding ends.

The problem of unequal treatment of boys and girls in schools and homes continues to affect hundreds of millions of people and undermines progress on multiple Sustainable Development Goals. Existing responses remain fragmented, under-resourced and poorly adapted to local contexts. A strong solution must operate effectively under severe constraints of skilled personnel, infrastructure, electricity and connectivity. It should define clear measurable outcomes, identify possible unintended harms, and demonstrate how the intervention can be sustained by local institutions long after initial funding ends.

Future progress on human development and planetary health depends on solving schools located too far for many children to reach. Conventional approaches have proven insufficient. The required intervention must integrate community knowledge, data and appropriate technology while remaining affordable, privacy-preserving and operable with minimal external support. Strong solutions will articulate measurable impact metrics, risk mitigation strategies, and a plan for sustained operation by local actors after the pilot phase.

Utility data are fragmented, pressure changes are poorly localized, and repairs compete with emergency work. Low-cost sensing, probabilistic fault localization, and outcome-based maintenance could let local operators prioritize the few failures that matter most. The opportunity is intentionally human-scale: a cooperative, clinic, workshop, school, or municipal team could pilot it within one locality and measure outcomes before expanding. Mathematical modeling can help with measure uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Vendors operate with thin margins and little historical data. Lightweight forecasting, shared cold storage, and cooperative purchasing could convert neighborhood-level signals into practical decisions without requiring enterprise software. The opportunity is intentionally human-scale: a cooperative, clinic, workshop, school, or municipal team could pilot it within one locality and measure outcomes before expanding. Mathematical modeling can help with allocate uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

The technical problem is coupled with a social allocation problem: production varies, meters may be imperfect, and residents need rules they trust. Tariff design, optimization, and transparent settlement tools could make shared generation investable. The opportunity is intentionally human-scale: a cooperative, clinic, workshop, school, or municipal team could pilot it within one locality and measure outcomes before expanding. Mathematical modeling can help with forecast uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Frontline workers often face incomplete records, unreliable connectivity, and high consequences for missed deterioration. Decision-support models must be calibrated locally, auditable, and paired with referral logistics rather than treated as standalone AI. The opportunity is intentionally human-scale: a cooperative, clinic, workshop, school, or municipal team could pilot it within one locality and measure outcomes before expanding. Mathematical modeling can help with verify uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Teachers cannot manually inspect every error pattern, while generic adaptive apps often optimize clicks rather than mastery. Compact knowledge models and teacher-controlled workflows could make personalization affordable and pedagogically accountable. The opportunity is intentionally human-scale: a cooperative, clinic, workshop, school, or municipal team could pilot it within one locality and measure outcomes before expanding. Mathematical modeling can help with coordinate uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Good firms can be rejected because financial statements lag reality or assets are hard to pledge. Cash-flow inference, purchase-order verification, and risk-sharing products could widen credit while limiting fraud and over-borrowing. The opportunity is intentionally human-scale: a cooperative, clinic, workshop, school, or municipal team could pilot it within one locality and measure outcomes before expanding. Mathematical modeling can help with measure uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Patients waste time visiting multiple shops, while inventory data are private and substitution rules are complex. Privacy-preserving stock signals, route optimization, and pharmacist-led protocols could reduce search costs without creating a dominant intermediary. The opportunity is intentionally human-scale: a cooperative, clinic, workshop, school, or municipal team could pilot it within one locality and measure outcomes before expanding. Mathematical modeling can help with route uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Curb demand changes by hour and street, but regulations are often static and enforcement is inconsistent. Auctions, reservation systems, and fairness constraints could improve throughput while protecting accessibility and local commerce. The opportunity is intentionally human-scale: a cooperative, clinic, workshop, school, or municipal team could pilot it within one locality and measure outcomes before expanding. Mathematical modeling can help with preserve uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

The bottleneck is not only parts supply but identification, dimensions, safety, and liability. Open component ontologies, machine-vision matching, and verified refurbishment networks could create new revenue for local technicians. The opportunity is intentionally human-scale: a cooperative, clinic, workshop, school, or municipal team could pilot it within one locality and measure outcomes before expanding. Mathematical modeling can help with repair uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.