Este trabajo formó parte del Proyecto “Respuesta humanitaria a las necesidades de las comunidades más vulnerables afectadas por la crisis alimentaria prolongada y sequías recurrentes en el Corredor Seco centroamericano”, encargado por Acción Contra El Hambre y ejecutado por Acción Contra El Hambre, OXFAM, Trocaire, WeWorld GVC, Médicos del Mundo y Cooperazione Internazionale y el objetivo general es contribute to saving lives, alleviating suffering and reducing the social and economic impact caused by the protracted food and nutrition crisis of extremely vulnerable rural households in the Central American Dry Corridor, specifically in Guatemala, Nicaragua, Honduras and El Salvador.
To do so a fortnightly price monitoring system for basic foodstuffs was established (white maize, yellow maize, beans, rice, pound of chicken, dozen eggs) in CA4 to make recommendations on how the ECHO SAN CA4 project might need to adapt to changing market conditions and anticipate possible impacts on the food security of vulnerable populations. This is one of the most relevant tasks due to the impact that the increase in the price of basic foodstuffs has on household budgets, so we developed an algorithm that extracts information from two sources that were considered a priority: the Honduran Agricultural Products Market Information System (SIMPAH) and the Humanitarian Data Exchange (HDX) global database of food prices.
The process of obtaining and representing data on food prices in Central America based on a methodology developed by GIS4tech start generating the basis for a periodic analysis that allows a comparison with average prices according to available historical series, taking into account seasonal oscillations that can be considered normal. The graphs obtained from these analyses help to establish price anomalies they are either cyclical in nature or limited to a specific country or market.
The methodology consists of carrying out the download weekly food price reports in PDF format. Then, price extraction is performed using techniques scrappingThe aim is to extract the prices for each item and organise them in tables for later backup in relational databases.
