he activities undertaken by Ramani Huria over the last four years stood as a model for a Handbook for Community Urban Risk Mapping. By helping communities to map residential areas, roads, streams, floodplains, and other relevant features, projects like Dar Ramani Huria bring disaster prevention and response to areas that were previously off the map, literally. Doing so brings awareness of the need for flood prevention and risk reduction to the local level, while teaching participants valuable computer and mapping skills that they can put to use elsewhere.
The handbook addresses the process of community risk mapping as it was created in the context of Ramani Huria in Dar es Salaam. It is however not a mere summary or one-to one recording of the work done by Ramani Huria. Ramani Huria has become bigger that its original purpose. The process has already been exported to different arenas, in Tanzania and abroad, where it was used to create maps for post-earthquake disaster relief and disease control. The handbook therefore explains and illustrates the main elements of community risk mapping in a way that we hope it can assist others to implement such community and risk-oriented mapping projects elsewhere.
The handbook is available for download from this website and is also included in a free online course.
On the basis of the same practical lessons learned from Dar Ramani Huria an open online course has been established. The ‘Handbook for Community Urban Risk Mapping’ provides similar content to this course, but in a more narrative format. The course includes the concepts covered by Ramani Huria, structured as a self-learning course. The materials can be used by universities and schools to complement their curricula that are for instance related to geo-information science and urban planning. It provides basic and more advanced materials which allow it to be used as an entry-level course, but it also provides deeper knowledge and tools for those with substantial prior knowledge and education in the subjects. Some of the technical subjects mentioned in the handbook are therefore covered more in-depth in the online courseThe course is placed in the CANVAS learning Management System, allowing a global dissemination. If you want to take a look at the course you can access it here. You are free to take the course after a quick registration. The material is primarily designed to be taught by professionals who already have some knowledge and experience in open source mapping applications. If you already study in Tanzania in one of the topics related to community risk mapping you are likely to be confronted with this material by your teachers. The contents is however not about Tanzania per se. The processes explained are adaptable to many urban environments that are exposed to risks that affect the well-being of the urban community. Therefore, in case you would like to learn more about this subject or earn a certificate for the skills learned, do alert your teachers about this course.
⅔ of African residents are in slum areas which are not planned. Since the cities are growing fast in Africa, slums increases to cities in Africa every year. On the other hand, education system in Africa is given based on theory and curriculums which follow imaginations instead of real and practical problems. Therefore, many people in Africa access the same education system and therefore do the same way is used to solve African problems especially the increased Cities in Africa. Furthermore, data in Africa is become the unavailable to be used to solve African slums problems because more theory is used and actual data is not used to solve African issues.
Resilience Academy brakes that gape in order to build the skills for young people who are able to use the actual problem available to the real world and to the local community. It helps to use the available tools and technology which are free, cheap and easy to be used by young generation to solve real world problems not using the same ways it is being used before but being knowledgeable to integrate the tools and the problems available within the community and to solve the problem together. Resilience Academy facilitate to fill the gap on data availability through cheap and easy ways to collecting data and encourage the use of available data for decision making.
Tanzania Resilience Academy is the start of Resilience Academy campaign where universities in Tanzania are working together: 1. to shape the training materials which relate to the problem available in Tanzania, 2. to collect the new data and collect existing data which have been collected before and organise them into one geospatial platform to allow easy access, easy use and easy contribute from all the local sectors especially the young researchers and 3. to create the ecosystem which is exposed to understand the importance of existing problems in Tanzania and the use of cheap, easy and free tools available so that data can be generated and updated according the need and create the Cities which are resilient across the country.
Tanzania Resilience Academy was launched to the four university in Tanzania which are University of Dar es Salaam, Ardhi University, State University of Zanzibar and Sokoine University of Agriculture with the large international university network such as University of Turku, Delft University, University of Twente, etc. With the aim of deploying of Tanzania Resilience Academy by developing open access education and training materials which will match with the real problem in Tanzania, Coordinate the development of climate risk geodatabase which give more opportunity for university network and other stakeholder to visualise, access, update as well as use the updated and relevant data in order to make the cities in Tanzania more resilience.
We welcome all to support this initiatives which began in Tanzania but expands further in African Countries.
As a means of emergency response after a flooding event or inland inundation, flood mapping helps to estimate the extent of the flood on a large scale. It is a basis of coordinating appropriate damage assessment activities, and providing relief to the victims. This blog explains an approach of community flood response by community mapping methods and rapid assessment to determine extent and damage.
In responding to heavy rainfall on March, 3rd, 2019, that resulted in heavy flooding in some wards of Dar es Salaam Tanzania, the Ramani Huria team decided to conduct field mapping to engage affected communities with the aim of conducting a rapid assessment and producing impact maps. In these wards, community leaders identified a total of 1907 floodedhouses. The survey was conducted in three of the most affected wards as reported by local newspaper (Mwananchi). It appears that the impact was severe on these wards due to multiple river channels meeting at these places causing massive outflows to the residential areas as well as inadequate drainage and blockage due to improper dumping.
Ramani Huria visited the affected wards and worked closely with community leaders to conduct rapid survey and assessment of impacts by:
Conducting meetings with community leaders and identifying the affected areas on printed A1 maps of the specific places
Field visits to physically assess the situation, taking photos and geo-points in some of the affected areas using OpenDataKit Collect, a mobile application that is used for field survey.
The maps used to conduct this assessment are the risk identification maps that were produced by RH team during the 2018 July summer industrial training. As we reported earlier, the maps were produced for the aim of developing ward disaster management plans with the overarching goal of creating a resilient city.
The impact of the foods included loss of properties, destruction of houses, students missing schools for two days because the roads were flooded, and their school books/items were destroyed by the heavy flood. Although there were no casualties, the impact affected communities significantly. Other people evacuated to nearby places that were safe at the moment, but in all these wards there were no specified evacuation centers where citizens can run to when it floods. This calls for government, disaster responders, humanitarian organizations, NGO’s and the community in general to “think” and plan how they can make sure there are safe places to stay when it floods.
The objective of this practice was to identify the extent of flooding in the most affected wards as well as the affected infrastructure such as roads and settlements and impaired areas of interest, for example schools and hospitals. The Ramani Huria team will be actively disseminating this report within the affected communities, and working to facilitate dialogue with PO-RALG, the Red Cross, NGOs, World Bank, and other stakeholders to make use of the information for future mitigation efforts, rescue and relief activities in affected areas.
In recent years experts in disaster responses are hopeful for the future of satellite and mapping technology in responding to disaster. If a flood response map is well developed, what you really have here is a map of the future. It can help in predicting the impact of future flood events and help in mitigation measures too.
Simply by recording data from presently flooded areas can be useful when identifying areas at risk of future flooding. With climate change well underway, people are increasingly interested in predicting the ways that flooding will worsen.
Digital data such flood data needs to be (easily) accessible and downloadable data for disaster responders to act quickly and save lives. Thanks to local people, local devices (mobile phones) and open knowledge (free software like OpenDataKit and the skills to use it), they say information should become even more accessible in the years to come. Flood data also needs to be in online interactive maps that can be integrated with mobile applications for easy access. The Ramani Huria team will be willing to provide such data so as to help more people and develop effective flood mitigation measures.
Piloting solid management system on informal settlements by creating data sets for trash collection companies to help them in locating and track their clients
Dar es Salaam is one of the fastest growing cities in Africa. The population is expected to grow so much, that Dar es Salaam is projected to be the second largest city by population in the world by 2100, with a predicted population of 76 million, (according to World Population Review). The annual growth rate is expected to average 4.39% through the year 2020. In the next three years the population is expected to reach 5 million.
With this rate of rapid urbanization and population increase with 70% of its people living in informal settlements, waste management (solid waste in particular) is a serious problem. Concurrent with recent socio economic development, the quantity of solid waste generated has increased at a rapid rate. There have been policies and laws to guide solid waste management in Dar es Salaam but it has never been effective, such that people tend to dump solid waste any way they can as there is no proper and effective way of waste collection
Flooding in Dar es Salaam is mainly caused by blockage of the waterways, i.e. rivers, drains, streams, ditches, etc. People dump solid waste and cause such blockages. Materials like metal, plastics, and sometimes natural debris are being dumped causing flooding. Without proper and effective ways of managing waste, floods will continue to overwhelm the drainage system, overflowing into communities, In Tabata most houses are flooded due to blocked drains.
HOT, with their local partner OMDTZ and supported by the World Bank, decided to pilot a mapping activity in an informal settlement (Tabata Ward) similar to what they have done in formal areas (Mchafukoge and Kisutu wards) and create datasets that may help trash company collectors to effectively collect trash from their clients.
HOT and OMDTZ partnered with Joshemi Company Limited, a company dealing with trash collection in Tabata. Tabata is an administrative ward in the Ilala District. According to the 2002 census, the ward had a total population of 46,228. The ward is comprised of eight subwards [Mandela, Kisiwani, Tenge, Msimbazi Mama, Msimbazi Magharibi, Tabata, Matumbi and Mtambani]. It is mainly comprised of informal settlementsand is found along the Msimbazi River valley (the main flooding river in the city).
Joshemi Company has created a weekly schedule for every subward where they have to collect the solid waste. Residents and owners of business firms must pay a certain amount to the company depending on the size of the trash bag.
The Aim of Mapping
JCL needed to know the number of clients as it was very difficult to track them all, revenue flow and an effective feedback system on services provided by the company. The aim was shifting JCL’s analogue system of trash collection to a digital system by providing them with their own maps of clients’ locations and a system of tracking them. This way, JCL would improve their services to clients, increase their revenues and create an effective waste collection mechanism.
Pilot mapping was conducted in two subwards of Tabata Ward (Msimbazi Magharibi and Msimbazi Mama). As our policy has always relied on open source software, we used OpenDataKit (ODK) Collect and OpenMapKit (OMK) – an extension of ODK which is a free and open android application for data collection. The team worked with revenue collectors to conduct mapping as they have a better understanding of the area to ease the process of data collection.
The team prepared an excel sheet with ward, subward name, the name of mjumbe, location together with client information including name, phone number, month, amount and receipt ID. To ease the process, fake ID numbers were created to identify clients’ houses because in informal settlements there are no house numbers. The sheet was then printed and given to the mappers for data collection, data cleaningand processing.
Outcomes and Impact
The company has a full understanding of the location and number of clients and challenges that their clients face. As the company now knows the number of clients, they plan to improve their services by having more trucks and more trips. Before mapping, they were only serving 300 clients, and after mapping, they have come to a realization that there are 2000 clients that need to be provided with the service. This will not only increase the company’s revenue but also improve service to the citizens and keep the ward clean.
Johanes Petro, a mapping supervisor at OMDTZ is very positive about the initiative. He said,
“This initiative will lead to improved waste management as the company now knows they have many clients, they may double or triple services and the clients will be serviced accordingly. In turn, this will increase revenue to the company and improve services to citizens”. He added, “There is a need to replicate this process to all informal settlements in Dar es Salaam which will contribute to a sustainable and clean city as the system created is user friendly”
Note: Until now, our team is working with the revenue collectors to capacitate them on data use and help to establish the link between the excel sheet prepared and established layers of OMK.
Challenges in Data Collection
The team started the process of data collection with the revenue collectors, but the revenue collectors were a bit hesitant to provide full collaboration as they were fraudsters and printing counterfeit receipts. So they believed if the company is provided with reliable data and the exact number of clients under service, their stealing methods would be revealed. So they did not collaborate and the company fired them.
Mappers had to shift from working with revenue collectors to shina leaders, famously known as “wajumbe” – the hyper local leaders (the most granular level of administration that exists in Tanzania). These leaders are responsible to administer a small cluster of houses ranging from 50 to 200 houses, and they are citizens’ primary point of contact. So working with them is an advantage as they are well known and trusted by the community
What is Next?
Seeing the positive outcomes on the two pilot subwards, there is a need to extend the project to the remaining six subwards of Tabata and even to the whole city if we had the support and funding from different partners. Joshemi Company that we’re working with are also eagerly waiting for the extension to the remaining subwards as they understand the power of data now- they even decided to pay community leaders and wajumbe that were helping mappers on data collection.
If this process is replicated in the remaining wards of the city, trash collection will be easier, the city will be clean and may also reduce the intensity of flooding as it is normally caused by blocked drains and rivers. There is also a need to develop an integrated solid management system which is cost effective and that takes into account economic options for solid waste management like recycling. The community and the general public also need to take responsibility on the process by collaborating with waste collection companies because the benefits are reciprocal. Our mappers are working on solidifying relationships between clients and companies as there was observed drift among them.
After the risk identification process implemented in 228 subwards of the city, Ramani Huria is now going further to map the lowest level of administrative system that exists in Tanzania. To do this we have partnered up with Data Zetu to map hyperlocal boundaries in Dar es Salaam for better decision making. Finding people with exact addresses is nearly impossible, as most part of the city is unplanned. Therefore, mapping Dar es Salaam to such a detailed level will allow us to address issues at a neighborhood level for the first time. This is very important and will be used in different levels for decision making from individuals to the government.
Dar es Salaam is divided into 5 municipalities, 92 wards, and approximately 452 subwards (a subward is also known as a “mtaa” in Swahili). Within an mtaa there are further divisions known as “shinas” (which translates roughly to “branches” in English). Shinas are sometimes also referred to as a “Ten Cell”, since originally these areas were home to ten households. Now, due to increases in population, it tends to be between 30 and 200 households per shina. Each shina is administered by a ‘mjumbe’ (plural ‘wajumbe’ in Swahili).
Shinas were originally a political construct, related to the organization of specific political parties. However, wajumbe are increasingly functioning as non-partisan public servants, often the first (and in some cases only) point of interaction between citizens and government. Though the political character of shinas has not entirely vanished, we are finding increasing acceptance amongst citizens and leaders (of all political stripes) of the utility of hyperlocal boundaries being mapped and known to all.
Ramani Huria and Data Zetu have aimed to conduct hyperlocal mapping within 84 subwards of Dar es Salaam. From 13th September to now 128 hyperlocal boundary data have been collected and 106 have been cleaned and verified for final map production.
Ramani Huria Mapping Supervisor training university students on how to trace the hyperlocal boundaries and visualized map output. Photo credit: Godfrey Kassano-Ramani Huria
A student will need a smartphone/Android phone installed with a revised version of Open Data Kit (ODK) which allows tracing lines/polygons easily.
Mjumbe, who is a shina leader, works with a student (mapper) to trace the boundary of his/her shina – also explaining the possible uses of shinas to enhance collaboration and participation. A student mapper with mjumbe will walk around the boundary creating a polygon-like structure then fill the right information on the survey such as number of shina, name of shina mjumbe and others.
After tracing the shina boundary, mjumbe and mapper use the the printed aerial imagery as a field paper to compare what has been traced from the field with the image to make sure they have traced the correct boundary.
Then students will send a form/survey to the server for further processes.
Data will be downloaded from the server which will be digitized through QGIS software, analysed and a hyperlocal boundary map produced.
Students with shina leaders verifying the correctness of traced boundary on ODK with the printed aerial image of the subward before sending to server. Photo credit: Godfrey Kassano-Ramani Huria
Community leaders had their opinions on the process of mapping shinas and they are expecting these data will be used to benefit them as a community, which is actually the goal of collecting them. Subward chairperson had some thoughts:
“With shina mapping it will help us to solve different problems in our communities since people will be clear with the administrative boundaries of their local leaders. Am happy to work with this organization and hopefully my representatives have fully participated and they are also happy for the work that your doing.” Abdallah M. Simbili, Chairperson Liwiti Subward.
Shina mjumbe in Msimbazi Subward – Tabata Ward showing the student mapper his shina boundary during field data collection. Photo credit: Godfrey Kassano-Ramani Huria
Possible uses of Hyperlocal Maps
Help the ward officers to manage the areas by allowing the ward/subward/shina leaders to better understand the structure of their areas.
In case of emergencies (e.g. fire outbreaks or flooding), shina maps can be of help in responding to these disasters as the location of the target is known.
In hospitals, tracking people’s origin by identifying their shina number at the registry- this will help to track patients with diseases like cholera, or malnutrition in children.
Shinas help the local people to know their representatives on the subward level since most of local problems are solved from the shina level.
Locating Malnourished Children and Help with Intervention
Malnutrition remains one of Tanzania’s greatest human development challenges. Despite displaying seemingly ‘low’ and ‘acceptable’ rates of acute malnutrition, the burden of undernourished children is one of the highest in the East African Region. An estimated 450,000 children in Tanzania are acutely malnourished or weak, with over 100,000 suffering from the most severe form of acute malnutrition.
With one of the highest burdens of under nutrition in East and Southern Africa, it is not solely individual lives in Tanzania that are threatened, but also the economic advancement of the next generation that is at stake. Individuals – both adults and children – who experience varying levels of malnutrition will struggle to take advantage of opportunities in, for example, education and employment that would enable them to improve their livelihoods. Understanding the devastating impacts associated with societal malnourishment, particularly amongst children, it is absolutely crucial that appropriate measures are put in place by those actors who are in a position to do so to mitigate such consequences.
Case Study: Amana Regional Referral Hospital in Dar es Salaam, Tanzania
Through the Data Zetu program, our team has been able to utilize the shina data collected across 36 subwards to support the Amana Hospital – one of 4 referral hospitals in Dar es Salaam serving between 800 and 1200 people each day – in improving their methods for collecting patient location data and enhancing patient origin tracing. One pediatric doctor at Amana Hospital, Dr. Omari Mahiza, has a keen interest in implementing a system that would enable him to record and track the location of the malnourished children he treats. By knowing more precisely where his patients are coming from, he is able to investigate why and the reasons for children’s malnutrition from one community to another and, in turn, uncover in more detail the causes that lead to this condition from one household to another.
For the past few months, the Data Zetu team has been working with the IT company who built the electronic medical record system at Amana Hospital to incorporate shina data and nearby landmarks into the system. The new fields in the e-health registry will enable staff to record more precise location data of patients who visit the hospital and support Dr. Mahiza and his colleagues in being able to pinpoint the home address of their patients more easily. Whether the motive is to investigate specific cases of malnutrition and the habits that lead to this condition or to locate the source of a seasonal outbreak, such as cholera, within a community, shina maps allow for this to happen more efficiently within a given community.
The next step for the Amana Hospital intervention is to provide training and capacity-building to local staff, such as registration attendants and nurses, about the importance and value of recording detailed patient location data in the e-registry. To ensure there is genuine understanding and interest among staff to record patient location data more systematically, our team will focus on facilitating discussions and highlighting use cases that exemplify the role that maps and other spatial tools play in strengthening public health in communities.
Beyond health interventions Shina maps can also be used in disaster management, facilitating disaster response as well as increasing the overall flood resilience of communities. For example, having more granular level administrative boundaries can increase precision in identifying affected areas and speed up the distribution of relief resources during and immediately after a flood event. Likewise having maps of shina boundaries may also prove useful to local administrators when directing and implementing infrastructural improvements.
Utengenezaji wa ramani za mipaka ya shina.
Baada ya mchakato wa kutambua maeneo yaliyo kwenye hatari kwenye mitaa 228 ya jiji la Dar es Salaam, Mradi wa Ramani Huria unaenda mbali zaidi na kutengeneza ramani za maeneo ya chini kabisa ya utawala yaliyopo Tanzania (shina). tunafanya hivi kwa kushirikiana na mradi wa Data Zetu kusaidia katika kufanya maamuzi. Kujua anwani za watu wanapoishi ni ngumu sana kwenye mji ambao haujapangwa. Hivyo kutengeneza ramani hizi kutasaidia kutatua matatizo mengi ya ramani kwa mara ya kwanza. Suala hili ni la muhimu sana na litatumika katika maamuzi kuanzia watu binafsi hadi ngazi ya serikali.
Dar es salaam imegawanyika katika manispaa tano, kata 92 na takribani mitaa 452. Ndani ya mtaa kuna mgawanyiko mwingine unaoitwa shina. Mashina pia hufahamika kama nyumba kumi, kwa kuwa mwanzoni mashina yalikuwa na nyumba kumii tu. Lakini kwa sasa kutokana na ongezeko la watu mijini mashina haya yana nyumba kuanzia 30 hadi 200. Kila shina huongozwa na mjumbe au balozi kwa vijijini.
Shina mwanzoni yalikuwa kisiasa,kulingana na mwongozo wa chama fulani. Hata hivyo wajumbe kwa sasawana kazi nyingi tofauti na za chama, kwanza ndio watu wa kwanza wanaounganisha wananchi na serikali. Japo suala la kisiasa katika shina halijapotea, ila tunaona wanaendelea kukubalika na wanajamii ana viongozi wa vyama vyote na matumizi ya mipaka hii ya shina kutengenezewa ramani na kufahamika kwa kila mmja.
Ramani Huria na Data zetu inalenga kutengeneza ramani hizi kwenye mitaa 84 ya Dar es salaam. Tangu tarehe 13 septemba hadi sasa data za mashina 106 zimekusanywa na kuchakatwa kwa ajili ya utengenezaji wa ramani.
Msimamizi wa utengenezaji wa ramani akitoa mafunzo kwa wanafunzi wa vyuo vikuu jinsi ya kukusanya mipaka na kuonyesha ramani ya mashina iliyokwisha japishwa; Picha- Ramani Huria.
Mbinu za Utengenezaji wa Ramani hizi.
Mwanafunzi atahitaji simu ya mkononi (Android) iliyowekwa programu ya ODK yenye marekebisho ambayo ina uwezo wa kuchukua taarifa za mistari kwa urahisi
Mjumbe, ambaye ni kiongozi wa shina atafanya kazi na mwanafunzi (aliyepata mafunzo) ili kupata mipaka ya shina- wakati huohuo mwanafunzi huyo atamueleza mjumbe juu ya matuizi mbalimbali ya ramani itakayo tengenezwa ili kuongeza ari ya usiriki. Mwanafunzi na mjumbe watazunguka katika mpaka wa shina na kujaza taarifa zote zinazotakiwa kama namba ya shina, jina la mjumbe nk.
Baada ya hatua hii, mjumbe pamoja na mwanafunzi watatumia picha ya anga iliyochapishwa ili kuhakikisha taarifa ya mipaka waliyokusanya kama ipo sahihi.
Mwanafunzi atatuma fomu/dodoso kwenye seva kwa ajili ya michakato mingine.
Taarifa hizo zitapakuliwa (download) kutoka kwenye seva ambazo zitafanyiwa kazi kwa kutumia programu ya QGIS, na kuchambuliwa ili kutengeneza ramani hizo za shina
Mwanafunzi akiwa na kiongozi wa shina wakihakiki mipaka iliyochukuliwa kwa kulinganisha picha ya anga na mpaka uliochorwa kwenye programu ya ODK; Picha Ramani Huria
Ufahamu wa Jamii.
Wanajamii walikuwa na mawazo tofauti tofauti kuhusu mchakato huu na wana matarajio makubwa kuwa data hizi zitatumika kwa ajili ya jamii husika, na hili ndilo lengo. Mwenywkiti wa mtaa wa Liwiti alikuwa na haya ya kusema:
“Ramani za mashina zitasaidia kutatua matatizo mbalimbali kwa kuwa watu watafahamu vizuri mipaka yao. Nina furaha kubwa kufanya kazi na shirika hili na ni matumaini yangu wawakilishi wangu amewapa ushirikiano mkubwa, na wamefurahi kufanya kazi nanyie” Abdallah M. Simbili, mwenyekiti wa mtaa- Liwiti
Mjumbe wa mtaa wa msimbazi- Kata ya Tabata akimuonyesha mwanafunzi mpaka wa shina lake wakati wa ukusanyaji taarifa. Picha: Ramani Huria.
Matumizi ya Ramani Hizi.
Itawasaidia watendaji wa mitaa kuelewa vizuri maeneo wanayo ongoza.
Kipindi cha dharura (kama moto au mafuriko), ramani hizi zinaweza kutuikaa kutoa misaada ya haraka kwa kuwa eneo halisi la tukio linafahamika.
Kwenye hospital, kujua watu wanapotoka kwa kujua namba za mashina katika programu ya usajili kuweza kujua ueneaji wa magonjwa kama kipindupindu na utapiamlo kwa watoto.
Kusaidia jamii kujua wawakilishi wao katika jamii kwa kuwa migogoro mingi hutatuliwa na viongozi hawa.
Kufahamu Maeneo ya Watoto wenye Utapia mlo na Kusaidia kwenye Harakati
Utapiamlo bado ni mojawapo ya changamoto kubwa za maendeleo ya binadamu Tanzania. Licha ya kuonekana/kusadikika viwango vya “chini” na vya “kukubalika” vya utapiamlo mkubwa, mzigo wa watoto wasio na chakula ni mkubwa Afrika Mashariki. Inakadiriwa watoto 450,000 nchini Tanzania wamepungukiwa na hawana nguvu, wakati zaidi ya watoto 100,000 huteseka kutokana na aina kali zaidi ya utapiamlo mkubwa.
Pamoja na mzigo mkubwa wa lishe Afrika Mashariki na Kusini mwa Afrika, sio tu maisha ya mtu binafsi nchini Tanzania ambayo yanatishiwa, lakini pia maendeleo ya kiuchumi ya kizazi kijacho yanahusika. Watu – wote wazima na watoto – ambao wana uzoefu wenye uzoefu tofauti tofauti wa janga la utapiamlo wajitahidi kutumia fursa, kwa mfano, elimu na ajira ambayo itawawezesha kuboresha maisha yao. Kuelewa athari mbaya zinazohusiana upungufu wa chakula, hususani miongoni mwa watoto, ni muhimu sana na hatua zinazofaa zichukuliwe na watendaji ambao wana uwezo wa kufanya hivyo ili kupunguza madhara hayo.
Eneo la mfano; Hospitali ya Rufaa- Amana Dar es Salaam, Tanzania
Kupitia mradi wa takwimu za Data Zetu, timu yetu imeweza kutumia data ya mipaka ya shina iliyokusanywa kwenye mitaa36 ili kuunga mkono Hospitali ya Amana – moja kato ya hospitali nne za rufaa Dar es Salaam zinazohudumia watu kati ya 800 na 1200 kila siku – katika kuboresha njia zao za kukusanya data ya eneo la mgonjwa na kuimarisha ufuatiliaji wa taarifa za mgonjwa anapotoka. Daktari mmoja wa watoto katika Hospitali ya Amana, Dk. Omari Mahiza, ana hamu kubwa ya kutekeleza mfumo ambao utamwezesha kurekodi na kufuatilia maeneo wanayotoka watoto wenye utapiamlo anaowatibu. Kwa kujua zaidi ambapo wagonjwa wake wanatoka, anaweza kuchunguza kwa nini na sababu za utapiamlo wa watoto kutoka kwenye jamii moja hadi nyingine na, kwa upande mwingine, kujua kwa undani sababu zinazosababisha hali hii kutoka kaya moja hadi nyingine.
Kwa miezi michache iliyopita, timu ya Data Zetu imekuwa ikifanya kazi na kampuni ya IT ambayo imejenga mfumo wa kurekodi wagonjwa kwa njia ya kielektroniki katika Hospitali ya Amana ili kuingiza data ya shina na alama muhimu zinazotambulisha eneo (landmarks) kwenye mfumo huo. Sehemu mpya itakayoongezwa katika programu hiyo ya usajili wa kielektriniki utawawezesha wafanyakazi kurekodi data sahihi ya eneo la wagonjwa ambao wamefika hospitalini na kumsaidia Dk. Mahiza na wenzake kuwa na uwezo wa kubainisha anwani ya wagonjwa wao kwa urahisi. Ikiwa lengo ni kuchunguza matukio maalum ya utapiamlo na tabia zinazosababisha hali hii au kupata chanzo cha kuzuka kwa magonjwa ya msimu, kama vile kipindupindu, ramani za shina zitawezesha hili lifanyike kwa ufanisi zaidi katika jamii husika.
Hatua inayofuata kwa Hospitali ya Amana ni kutoa mafunzo na kujenga uwezo kwa wafanyakazi wa ndani, kama wahudumu wa usajili na wauguzi, kuhusu umuhimu na thamani ya kurekodi data ya eneo anapotoka mgonjwa wakati wa usajili. Ili kuhakikisha kuna uelewa wa kweli na maslahi kwa wafanyakazi wa kurekodi data ya eneo wanapotoka kwa ufanisi zaidi, timu yetu itazingatia kuwezesha majadiliano na kuonyesha matumizi ya ramani kwa kuonyesha mifano dhahiri ya jinsi gani taarifa hizi zinaweza kuimarisha huduma za afya kwa jamii.
Zaidi ya mipango ya afya, ramani pia zinaweza kutumika katika usimamizi wa maafa, kuwezesha mipango ya haraka ya kukabiliana na maafa na kuongeza ustawi katika kupambana na mafuriko kwa jamii. Kwa mfano, kuwa na mipaka ya utawala katika ngazi ya chini zaidi inaweza kuongeza usahihi katika kutambua maeneo yaliyoathirika na kuharakisha usambazaji wa misaada wakati na baada mafuriko. Vivyo hivyo kuwa na ramani za mipaka ya shina inaweza kuwa na manufaa kwa watendaji wa mitaa wakati wa kuongoza na kutekeleza maboresho ya miundombinu.