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Country: Haiti Source: World Food Programme Please refer to the attached file.

Countries: Ukraine, Georgia Source: World Vision Please refer to the attached file. The “Batkivska Opora” (Parenting in Crisis) Chatbot Learning Report documents the pilot implementation of an innovative digital solution designed to support families affected by the war in Ukraine and displacement in Georgia. Developed through a strategic partnership of World Vision Ukraine Crisis Response with World Vision Middle East and Eastern Europe Region (WV MEER), World Vision Georgia, Parenting for Lifelong Health (PLH), and the University of Oxford, the chatbot serves as a “pocket support tool”, delivering evidence-based parenting guidance directly to caregivers via Telegram. The pilot, conducted between May 2025 and March 2026, was launched in response to a critical gap in mental health and psychosocial support (MHPSS). With 84% of households reporting child distress and caregivers facing significant barriers to in-person services, the project aimed to provide accessible, automated, and culturally adapted support for those living under prolonged stress. This report outlines the technical structure of the 11-module curriculum, covering topics from self-care and grief to safety in shelters, and evaluates user engagement across 15 centres in Ukraine and Georgia. By synthesising feedback from over 300 initial users, this document offers vital insights into the scalability of digital humanitarian tools.

Country: Afghanistan Sources: Agency Coordinating Body for Afghan Relief and Development, Humanitarian Advisory Group Please refer to the attached files. This study examines the current state of coordination between non-governmental organizations (NGOs) and private sector actors in Afghanistan, focusing on how these actors engage across humanitarian and development programming and how such engagement contributes to localisation and sustainable development outcomes. The evidence shows that while collaboration exists across multiple sectors, it remains largely fragmented, informal, and operational, with limited institutionalisation for long-term strategic partnership development. Across NGOs collaboration is most commonly observed through bilateral partnerships, donor-facilitated coordination, government-mediated contracting, and informal relationship-based arrangements. These partnerships are most active in agriculture, water, sanitation and hygiene (WASH), telecommunications, small and medium enterprise (SME) development, and service delivery sectors, where private actors mainly contribute technical expertise, implementation capacity, or market access. NGOs typically retain leadership over programme design and resource allocation, while private sector actors are more frequently engaged through procurement and service delivery contracting but rarely as strategic partners involved in programme design, co-investment, or shared accountability. As a result, collaboration is strongest at the operational level, moderate at the programmatic level, and weakest at the system level where policy, investment, and coordination structures are defined. A key pattern in the evidence is that partnership effectiveness tends to be perceived more positively at the relationship and operational level where collaboration delivers clear value in livelihoods, enterprise support, or service provision than at the system level, where informants with broader coordination and policy roles were more skeptical about overall effectiveness. Partnerships demonstrate clear value where they deliver practical results such as vocational training, micro, small and medium enterprise (MSME) support, infrastructure delivery, and service provision. Key informants noted, effectiveness is strongest when collaboration is supported by flexible procurement, cash-based approaches, strong community networks, and technical leadership from private actors such as vocational training, MSME support, infrastructure delivery, and service provision. Evidence also highlights that integrated and area-based programming, along with neutral conveners, such as organisations or platforms capable of facilitating dialogue, building trust, and aligning incentives across NGOs, private sector actors, and government, helps improve alignment and coordination. More successful cases combine market linkage, capacity building, and longer-term engagement, while weaker models are associated with short-term, fragmented, and poorly contextualised interventions. Despite positive examples, the overall system is constrained less by lack of willingness among actors than by a weak enabling architecture — fragmented coordination mechanisms, short funding cycles, unequal risk distribution, and regulatory uncertainty that collectively shape how partnerships are designed and sustained. Coordination mechanisms remain fragmented and weakly institutionalised, with no consistent platform for structured partnership development. Key constraints include unclear policy and regulatory frameworks, fragmented institutional mandates, weak PPP structures, and limited legal clarity for SMEs and women-led enterprises. Financial constraints such as short-term funding cycles, rigid donor modalities, limited risk-sharing, and delayed payments further restrict effective collaboration. These are reinforced by market-level challenges, including weak value chains, limited infrastructure, low access to finance, skills gaps, and broader political and economic instability. Collaboration contributes positively to inclusion, particularly for women and rural communities, through livelihoods, MSME development, vocational training, and targeted cash-for-work programmes. Women’s economic participation is the most visible area of impact, especially in small enterprises and agriculture-based activities. However, inclusion of persons with disabilities and other vulnerable groups remains limited. Outcomes are strongest when interventions are deliberately designed, locally contextualised, and linked to markets and sustainable income opportunities rather than short-term assistance. The findings indicate that localisation in Afghanistan is developing in form but remains constrained for local actors including NNGOs and private sector. Primary KII data from across stakeholder groups confirms that private sector actors are present but not consistently empowered, consulted but not given a decision-making role, and relied upon for delivery without corresponding influence over strategy or resources while decision-making authority, programme design, and financial control remain concentrated with NGOs and donors. This pattern mirrors what the ACBAR/LTWG Localisation Baseline Assessment found for NNGOs, and this study’s primary data validates that it extends to locally owned private sector actors as well. Strengthening localisation requires shifting power to local actors through deeper participation in design and budgeting, improved access to finance, stronger institutional coordination, and more flexible funding mechanisms. The evidence suggests that localisation will remain limited unless constraints in funding, policy, and coordination are addressed.

Country: Jamaica Source: World Food Programme Please refer to the attached file.

Country: Ukraine Source: KoboToolbox Please refer to the attached file. Report on the civilian effects of attacks on energy infrastructure in Ukraine. Drawing on a large-scale survey, the study documents how power outages affected civilians’ health, mental health, education, and livelihoods, as well as how civilians coped and prepared for energy blackouts. The report offers key recommendations for mitigating and responding to the humanitarian consequences of power outages.

Countries: World, American Samoa, Cook Islands, Fiji, French Polynesia (France), Guam, Kiribati, Marshall Islands, Micronesia (Federated States of), Nauru, New Caledonia (France), New Zealand, Niue (New Zealand), Northern Mariana Islands (The United States of America), Palau, Papua New Guinea, Pitcairn Islands, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, Vanuatu, Wallis and Futuna (France) Source: World Health Organization Please refer to the attached file. Alerts: 3 SARI alerts (Tonga, Vanuatu, Samoa) 1 AFR alert (Tonga) Respiratory virus epidemiology in the Pacific Island Countries for EPI – WK 15, 2026 PSSS, EPI -WK15, 2026 Influenza-like Illness (ILI), Severe Acute Respiratory Illness (SARI), and COVID-19-like cases are compared to WK14, 2026 and tabulated below for easy comparison (▼ Decreasing ▲ Increasing ● Stable). To provide additional context on the figures and trends, the percentage of sentinel sites reporting WK14 & WK15, 2026 is also included. Reporting below 80% is indicated as ▼low reporting and – is no report available. Please refer to seasonal-influenza for Pacific Island Countries and Areas – ILI Surveillance. Attached is the weekly bulletin for your reference and additional information.

Country: Afghanistan Source: Data for Afghanistan Please refer to the attached file. Methodology Baseline poverty lines Poverty lines are drawn from Afghanistan’s Income, Expenditure and Labour Force Survey 2020 (IE&LFS 2020), conducted by the National Statistics and Information Authority (NSIA). Poverty lines are estimated per person per month. The food poverty line is set at the cost of obtaining 2,100 kcal per person per day from a reference basket reflecting actual Afghan food consumption. The reference basket was priced at Central Urban (Kabul) prices in Q1 2019 (October–December 2019). Its value was AFN 1,330 per person per month. Non-food poverty lines are area-specific (14 areas covering Afghanistan’s 8 regions × urban/rural residence), and priced in Q1 2019 (October–December 2019) prices at the time of the survey (IE&LFS 2020). Updating to current prices The food poverty line is updated monthly using the Kabul food CPI from NSIA, maintaining consistency with the Kabul price base of the original survey. The non-food poverty line for each area’s associated provinces is updated using the province-level non-food CPI from NSIA, hence preserving the spatial variation estimated in 2019-2020. This approach produces a total poverty line per person per month in current Afghani for each province × urban/rural residence combination. Household MEB calculation The Minimum Expenditure Basket (MEB) for a household is the total poverty line per person multiplied by household size. A self-coverage deduction can be applied to reflect the portion of minimum needs a household can meet from its own income or assets, which is subtracted before calculating the recommended transfer value. Vulnerability buffers Percentage uplifts are applied to reflect the additional expenditure burden faced by vulnerable household types: female-headed households, internally displaced persons (IDPs), returnees, refugees, households with a disabled member, disaster-affected households, and households carrying debt. Buffer values shown are indicative placeholders. However, empirically derived values from your own work could be used to replace them for programmatic use. Two stacking options are provided: multiplicative (buffers compound independently) and maximum-only (most conservative approach). Data sources IE&LFS 2020 poverty lines — NSIA Monthly food and non-food CPI by province — NSIA (latest release)