The USAID business forecast contains in-advance information about opportunities to partner with USAID. USAID regularly collaborates with host countries, beneficiaries, U.S. government agencies, international donors, and implementing partners to ensure that we effectively address development needs in the countries where we work. This dataset is continually updated from the source data found at https://www.usaid.gov/business-forecast

The USAID business forecast contains in-advance information about opportunities to partner with USAID. USAID regularly collaborates with host countries, beneficiaries, U.S. government agencies, international donors, and implementing partners to ensure that we effectively address development needs in the countries where we work. This dataset is continually updated from the source data found at https://res1wwwd-o-tusaidd-o-tgov.vcapture.xyz/business-forecast

The Global Forecast System (GFS) forecast precipitation data at 37.5km resolution is created at the NOAA Climate Prediction Center for the purpose of near real-time usage by the national and international relief agencies and the general public. The users of this data include the U.S. Geological Survey (USGS), the U.S. Agency for International Development (USAID), the Joint Agricultural Weather Facility (JAWF) and the national Meteorological Centers in Africa, Asia and South America. The data is disseminated in the binary format as well as in the form of shape and tiff files for use by the GIS community. This data has seven individual 24-hour accumulated precipitation amounts (in millimeters) corresponding to the seven forecast days and one for the grand total of accumulated 7day total precipitation (in millimeters). Thus, the represented forecast fields have 8 Geotiff files and 8 shape files. All these files are zipped into a single file (per day).

The Global Forecast System (GFS) forecast 0-10cm soil-moisture data at 37.5km resolution is created at the NOAA Climate Prediction Center for the purpose of near real-time usage by the national and international relief agencies and the general public. The users of this data include the U.S. Geological Survey (USGS), the U.S. Agency for International Development (USAID), the Joint Agricultural Weather Facility (JAWF) and the national Meteorological Centers in Africa, Asia and South America. The data is disseminated in the binary format as well as in the form of shape and tiff files for use by the GIS community. The soil moisture data in the GIS format can be accessed at the online linkage provided above.

This asset contains the Short-Term (ST) Load Forecast Data and Xesco Energy Sent Out - Maximum Demand (ESO-MD) Load Data from the Southern Africa Energy Program

This dataset contains spatial surfaces with the number of flooding events detected per year using satellite imagery in Honduras between 2017 and 2022. In addition, the accumulated annual flood events detected for the analyzed six-year period is also published. They are classified into the following three (3) classes according to the number of events detected: 1: one flood event, 2: two flood events, and 3: three or more flood events. The data was elaborated under the project named ‘Water Management Activity: Appropriation of the “Agua de Honduras” platform by local and national stakeholders to improve country capacities in water resource planning in Honduras’, an initiative funded by the United States Agency for International Development (USAID).

This dataset was developed by the National Renewable Energy Laboratory (NREL) for the U.S. Agency for International Development's (USAID) South Asia Regional Initiative for Energy Cooperation (SARI/E). The dataset contains graphical files of seasonal and diurnal data from over 50 surface weather stations in .pdf format in Afghanistan. The data were output in Geographic Information Systems (GIS) format and incorporated into a Geospatial Toolkit (GsT). The GsT allows the user to examine the resource data in a geospatial context along with other key information relevant to renewable energy development, such as transportation networks, transmission corridors, existing power facilities, load centers, terrain conditions, and land use.

License Info

DISCLAIMER NOTICE This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data. Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data.

Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data.

THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN CONNECTION WITH THE ACCESS OR USE OF THE GIS DATA.

The User acknowledges that access to the GIS data is subject to U.S. Export laws and regulations and any use or transfer of the GIS data must be authorized under those regulations. The User shall not use, distribute, transfer, or transmit GIS data or any products incorporating the GIS data except in compliance with U.S. export regulations. If requested by DOE/NREL, the User agrees to sign written assurances and other export-related documentation as may be required to comply with U.S. export regulations.

In order to characterize the historical climate for the Western Honduras region, it was developed monthly surfaces by years through spatial interpolation and available records of weather stations. The interpolated surfaces were generated at 1-km of spatial resolution (30 arc-seconds) for monthly precipitation (1981-2015), and minimum and maximum temperature (1990-2014). It was followed the method described by Hijmans et al. (2005), using data from: (1) the DGRH (General Direction of Water Resources of the Honduran Ministry of Natural Resources); (2) the National Oceanic and Atmospheric Administration (NOAA), including data from the Global Historical Climatology Network (GHCN) and the Global Surface Summary of the Day (GSOD); and (3) the ENEE (National Electric Power Company of Honduras). In some areas with low weather station density, it was added pseudo-stations from CFSR (Climate Forecast System Reanalysis) for temperature (Ruane et al., 2015) and CHIRPS (Climate Hazards Group InfraRed Precipitation with Station; Funk et al., 2015) for precipitation. For future climates, it was performed a statistical downscaling (delta method or change factor) process based on the sum of the anomalies of GCMs (General Circulation Models), to the high resolution baseline surface (the 20-yr normal) at monthly scale (Ramirez & Jarvis, 2010). It was used data from ~20 GCMs from the IPCC AR5 (CMIP5 Archive) run across two Representative Concentration Pathways (RCP 2.6 and 8.5), for the reported IPCC future 20-year periods (IPCC, 2013): 2026-2045 (2030s) and 2046-2065 (2050s).

Important Note: This item is in mature support as of June 2024 and will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.The GEOGloWS ECMWF Streamflow System represents a daily 51-member ensemble streamflow forecast for over 1 million reaches across the globe. Gridded surface runoff, provided by the European Centre for Medium-range Weather Forecasting (ECMWF), is downscaled and routed to the streams using the Routing Application for Parallel computation of Discharge (RAPID). This animation layer shows the first 6-days of a 15-day forecast at 3-hr intervals. Additionally, a 40-yr historical simulation was produced based on ECMWF’s ERA5 dataset. From this historical simulation , return periods for each reach are calculated and used to color the stream segments when/where events exceed these thresholds. Credits: This forecast model was produced as part of the GEOGloWS Partnership with collaboration from BYU, ECMWF, esri, NOAA, NASA, SERVIR, USAID, ICIMOD, JRC, Copernicus, World Bank, and Microsoft Azure.What can you do with this layer?This map service is designed for fast data visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the forecast data sequentially using the time slider, which is set to three hour intervals by default by Enabling Time Animation. This layer type is not recommended for use in analysis.Revisions:Dec 15, 2020: Updated 'flowstyle' field values from color names: 'blue', 'yellow', 'purple', ... to Return Period values. This now reports '0', '2', '5', '10', '25', '50', and '100' indicating the forecasted return period. The symbology has also been extended to better depict the relevant state of each reach using these periods.

Overview

New York, NY – Aug 07, 2025 : The Global HIV Drugs Market is projected to reach US$ 53.5 Billion by 2034, growing from US$ 34.8 Billion in 2024, with a CAGR of 4.4% from 2025 to 2034. HIV drugs, mainly used for Antiretroviral Therapy (ART), are designed to manage HIV and slow disease progression. These drugs don't cure HIV, but they lower the viral load and enhance the quality of life. ART typically combines different classes of drugs, such as NRTIs, NNRTIs, protease inhibitors, integrase inhibitors, and entry inhibitors.

According to UNAIDS 2023, around 39.9 million people globally are living with HIV, with 53% being female. By the end of 2023, 30.7 million individuals were receiving ART, covering 77% of those in need. Awareness campaigns have been effective, with 86% of people knowing their HIV status. However, about 5.4 million people remain unaware of their condition. Despite the progress, AIDS-related deaths reached 630,000 in 2023, showing a significant decrease since the 2004 peak.

The HIV drugs market is driven by rising awareness and innovations in drug formulations. For example, oral PrEP (Pre-exposure Prophylaxis) with tenofovir-based regimens is widely recommended by the World Health Organization. New developments like injectable PrEP, such as cabotegravir (Apretude), offer protection every two months. Additionally, lenacapavir, approved by the U.S. FDA in June 2025, provides nearly 100% efficacy with biannual dosing. These innovations are transforming HIV prevention and treatment landscapes.

PEPFAR's data from September 2024 shows that 20.6 million people, including 566,000 children, are receiving ART under its programs. The initiative also facilitated 2.5 million new PrEP initiations and 83.8 million HIV tests. However, potential funding threats to PEPFAR and USAID could undermine global efforts. UNAIDS warns that interruptions in prevention programs could lead to approximately 2,300 new HIV infections daily. Maintaining funding and support is critical for sustaining progress in HIV treatment and prevention.

The demand for discreet and convenient access to HIV medications is also reshaping the market. In August 2024, East Sussex launched an online platform to provide PrEP privately. Such digital health innovations improve medication adherence and expand reach to underserved populations. Single-tablet regimens and long-acting injectables are simplifying treatment protocols. These innovations help reduce pill burden, improve treatment adherence, and enhance long-term disease management, which will continue to drive market growth.

USAID tasked WASHPaLS with assessing the effects of COVID-19 on WASH access in its high priority (HP) and strategy-aligned countries. The assignment sought to both characterize the current state of affairs as well as to forecast near-term future trends. The activity conducted key informant interviews with WASH product and service providers, government officials, donors and WASH program implementers, as well as SMS-based surveys of over 3,000 randomly selected individuals in 6 deep dive countries. SMS surveys were conducted by the mobile-base research firm GeoPoll. The survey could be easily read and filled out with a basic feature phone (non-smartphone) and was offered to potential respondents incentivized by a modest offer of top-up credit. The instrument consisted of 33 questions, with skip patterns that meant that a respondent typically saw on the order 20-25 questions. The six deep dive countries in this data asset include DRC, Ghana, Kenya, Mozambique, Rwanda and Senegal. Summary data is available via the links under "References," in the Common Core section, below.

The dataset comprises a panel of 1,612 agricultural households located across 75 communities in the departments of Huehuetenango, Quiche, and San Marcos in Guatemala that were both interviewed in person in November-December 2019, for the baseline survey, and over the phone in a follow-up survey in May-June 2020 and May-June 2021 to assess the impacts of COVID-19 on livelihoods and food security. This is only subset of the data which is constructed from these three surveys and consist limited information household socioeconomic characteristics, dwelling characteristics, income, asset ownership, agricultural activities, changes in food consumption, food insecure experiences, and self-reported preferences. The full dataset is planned for release in near future after completion of few more rounds of follow-up survey.

The GEOGloWS ECMWF Streamflow System represents a daily 51-member ensemble streamflow forecast for over 1 million reaches across the globe. Gridded surface runoff, provided by the European Centre for Medium-range Weather Forecasting (ECMWF), is downscaled and routed to the streams using the Routing Application for Parallel computation of Discharge (RAPID). This animation layer shows the first 6-days of a 15-day forecast at 3-hr intervals. Additionally, a 40-yr historical simulation was produced based on ECMWF’s ERA5 dataset. From this historical simulation , return periods for each reach are calculated and used to color the stream segments when/where events exceed these thresholds.Credits: This forecast model was produced as part of the GEOGloWS Partnership with collaboration from BYU, ECMWF, esri, NOAA, NASA, SERVIR, USAID, ICIMOD, JRC, Copernicus, World Bank, and Microsoft Azure.What can you do with this layer?This map service is designed for fast data visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the forecast data sequentially using the time slider, which is set to three hour intervals by default by Enabling Time Animation. This layer type is not recommended for use in analysis.Revisions:Dec 15, 2020: Updated 'flowstyle' field values from color names: 'blue', 'yellow', 'purple', ... to Return Period values. This now reports '0', '2', '5', '10', '25', '50', and '100' indicating the forecasted return period. The symbology has also been extended to better depict the relevant state of each reach using these periods.

This dataset is a cleaned version of the Republic of Zambia Ministry of Agriculture & Livestock and Central Statistical Office Crop Forecast Survey for four years from 2010/2011 through 2013/14, covering small- and medium-scale farms. It may contain some variables computed from the original CFS variables. The dataset was used for purposes of calculating crop cost and return budgets for improved versus local varieties of maize, with a spatial (geographic/administrative) breakdown.

The gridded yearly climate data (5-year moving averages) were developed from weather station observations (from IDEAM and Cenicafe) for the period 1980 to 2010, at 500 m spatial resolution, for monthly precipitation, monthly minimum temperature and maximum temperature, following the method of Hijmans et al. (2005). In areas with low station density and low interpolaton quality, weather observations were complemented with pseudo-stations from AgMERRA for temperature (Ruane et al., 2015) and CHIRPS (Funk et al., 2015) for precipitation. The results were aggregated into decadal and 30-yr climatology data. Future climate data was developed by downscaling CMIP5 projections from 14 General Circulation Models (GCMs) for all four RCPs (RCP 2.6, 4.5, 6.0 and 8.5; IPCC, 2013) following the method of Ramirez-Villegas and Jarvis (2010). Data were for 2020s and 2030s, which reflect the 10 and 15-year coffee planning cycles. Using the monthly data, we developed climate indicators for modelling following expert knowledge (from Cenicafe) and literature (CENICAFE, 2016) for specific seasons (DJF, MAM, and SON) associated with phenological events: mean temperature range (thermal amplitude), thermal time, mean temperature, temperature seasonality, precipitation seasonality and reference evapotranspiration.

Site-specific watershed analysis requires site-specific meteorological data. Due to high spatial and temporal variability nature, collecting in-situ weather data is essential for modeling biophysical processes and understanding the biophysical condition of watersheds. In addition, site-specific weather information by itself is useful for improving agricultural practices in selected Africa RISING sites. This data study contains weather-related data which was generated to support various analysis in Africa RISING sites. The data included all the weather elements i.e. precipitation, soil moisture (volumetric water content, soil temperature, cation exchange capacity (CEC)), wind (direction, speed, and gusts), air temperature, solar radiation, and relative humidity. These data were collected at two sites (kebeles) for each Africa RISING sites. They were collected at 15 minutes interval since September 2014. The data collection is still ongoing.

Farmers are registered under the FarmerLink program, entitled to receive both SMS and IVR messages from time to time on coconut and cacao good agricultural practices, market price information, pest and disease information, and weather forecasts. Collects info about the farmers.