Remote Integrated Phase Classification during the COVID-19 pandemic: experiences from Madagascar
By Smaila Gnegne, Moussa Moctar, Andrianianja Raonivelo, Desire Rwodzi, Mara Nyawo and Douglas Jayakasekaran
Smaila Gnegne is a health statistician with over nine years’ experience in the monitoring and evaluation of health and nutrition interventions. He is currently working with UNICEF in Madagascar on nutrition monitoring and previously worked with the National Statistical Institute and Médecins Sans Frontières (MSF) in West Africa.
Moussa Moctar is a Nutrition Analyst with the Integrated Phase Classification (IPC) Global Support Unit (GSU) hosted at the Food and Agriculture Organization (FAO) in Rome, Italy where he provides technical support to countries on IPC implementation.
Andrianianja Raonivelo is an agricultural engineer with two postgraduate diplomas in agronomy and risk and disaster management. He has 12 years’ experience working in the National Office of Disaster and Risk Management (BNGRC) and is Chairman of the IPC Technical Working Group and the National Vulnerability Assessment Committee of Madagascar.
Desire Rwodzi is a former Knowledge Management Officer with the Nutrition Section in UNICEF’s Eastern and Southern Africa Regional Office.
Mara Nyawo is a Nutrition Specialist with the UNICEF Eastern and Southern Africa Regional Office. She has worked for over 15 years in humanitarian and development contexts in sub-Saharan Africa.
Douglas Jayakasekaran is a Consultant Nutrition Specialist with IPC GSU. He has over 15 years of experience working in health and nutrition in both humanitarian and development contexts throughout Asia and Africa.
The authors would like to thank all those who contributed to providing information for this article including colleagues from the National Office of Disaster and Risk Management (BNGRC), the National Nutrition Office, Nutrition Service under the Ministry of Health in Madagascar, UNICEF and FAO Madagascar. Most importantly, we would like to thank the dedicated IPC Acute Malnutrition analysts in Madagascar who carried out the analysis exercise on which this paper is based. We would also wish to thank the European Civil Protection and Humanitarian Aid Operations and the United States Agency for International Development for their generous and continued contributions and support for IPC analysis in Madagascar.
The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of UNICEF or the IPC.
What we know: The Integrated food security Phase Classification (IPC) provides information to decision makers to address food insecurity; COVID-19 related movement restrictions meant that normal IPC methods could not be used.
What this article adds: In May 2020, the Madagascar Ministry of Health, UNICEF and other nutrition partners, together with the IPC Global Support Unit (GSU), leveraged existing technologies to conduct a virtual IPC analysis for acute malnutrition in six drought-prone southern districts in Madagascar. Adaptations made to the IPC methodology for the COVID-19 context featured the inclusion of already trained team members to reduce the length of orientation, utilisation and re-analysis of data collected just prior to lockdown to overcome challenges in data collection and the shifting of meetings from in-person to virtual. A number of assumptions were built into the analysis given the COVID-19 context including the likely negative impact on food systems and access to health services in the post-harvest period. Results of the analysis hypothesised the likely deterioration of the nutrition situation in all six districts beyond August 2020 with two districts being classified as IPC phase 3 or 4. The IPC analysis was largely deemed a success as a result of strong political will and support from nutrition partners and the IPC GSU. However, numerous challenges were noted including a reliance on historical data, a lack of global guidelines on remote facilitation at the time and internet connectivity challenges.
The Integrated food security Phase Classification (IPC) is a widely accepted mechanism for improving food security and nutrition analysis and decision making (http://www.ipcinfo.org/). Originally developed in 2004 in Somalia by the Food and Agriculture Organization's Food Security and Nutrition Analysis Unit (FSNAU), IPC has evolved over time and currently includes a range of classification scales, namely Acute Food Insecurity (IPC-AFI), Chronic Food Insecurity (IPC-CFI) and Acute Malnutrition (IPC-AMN) with each scale informing specific types of action needed to address food insecurity and malnutrition (IPC Global Partners, 2019). IPC results inform humanitarian response planning and are the main source of data for the Global Food Crisis Report.1 The IPC-AMN analysis provides decision-makers with key information to support activities that aim to decrease the prevalence of acute malnutrition. Specifically, it provides guidelines for the classification of areas in terms of the prevalence of global acute malnutrition (GAM) (thresholds for weight-for-height z-score (WHZ) and mid-upper arm circumference (MUAC)), estimations of the numbers of acutely malnourished children (by WHZ, MUAC and/or both), classifications of geographical areas in terms of severity of acute malnutrition and the identification of the key drivers of acute malnutrition.
The general approach for conducting IPC analysis is for stakeholders at national-level to gather primary and secondary data on food security and nutrition, after which they converge to discuss the results, facilitated by and together with technical support from IPC experts. However, this approach has not been feasible in many contexts since the outbreak of the COVID-19 pandemic due to restrictions on travel and gatherings which, at the same time, have resulted in widespread increases in food insecurity due to reduced livelihood activities and household incomes and disrupted supply chains. Four days after Madagascar first reported a case of COVID-19, in March 2020, the country was put on total national lockdown which included a ban on all regional and international travel and a total shut down of all non-essential activities in the cities of Antananarivo and Toamasina. It was therefore critical to find possible ways to understand the food security and acute malnutrition situation within this novel context.
The 10 southern-most drought-prone districts in the Greater South (Grande Sud) of Madagascar have historically had chronically high levels of both stunting (classified as very high at above 30%) and wasting (GAM levels classified as medium-high nationally at 5-10%, with some districts reaching 10-15%) (MICS, 2018). Given the chronic nature of nutrition vulnerability of populations in the southern parts of Madagascar, the Ministry of Health (MoH) and nutrition partners, including UNICEF, and together with the IPC Global Support Unit (GSU), leveraged existing technologies to conduct a virtual IPC analysis for acute malnutrition (IPC-AMN) for six districts of the Greater South in May 2020 (these six districts out of the 10 districts in the region were selected based on the level of data availability). This article highlights how the IPC-AMN analysis was conducted virtually in order to obtain an understanding of the level of malnutrition in the Greater South region of Madagascar.
Figure 1: IPC analysis for acute malnutrition
A four-stage approach was followed as described in Figure 12 with each stage described below.
Stage One: Planning
Typically each year, a planning exercise is conducted between country IPC Technical Working Groups (IPC-TWG) and the IPC GSU in order to determine the number and timing of IPC analyses for the year. This planning meeting took place towards the end of 2019 between Madagascar’s IPC-TWG and the Nutrition Cluster, after which it was agreed that an analysis would be conducted in October of 2020. Due to COVID-19, the planning was rapidly adjusted at the request of the Nutrition Cluster and the MoH to enable an analysis of the nutrition situation in districts affected by drought. The virtual methodology was jointly proposed by UNICEF and the IPC GSU and approved by the country IPC-TWG. This was the first time that such an approach had been piloted globally.
Under normal circumstances, IPC analysis usually takes 10 days (including four days of training at the beginning). To shorten the process, previously trained and certified participants were selected to make up the team which reduced the length of the process by four days. This was helpful to ensure that the participants remained motivated and committed during the analysis while using virtual means of communication.
Stage two: Preparation for analysis
A country core group, comprised of one IPC-GSU focal point and four national staff as part of the national IPC-TWG (representatives from MoH, the National Nutrition Office, UNICEF and the National Office of Disaster and Risk Management), prepared relevant tools, data and indicators for analysis. This group met three times virtually using Zoom with technical and financial support from UNICEF. Data was collated on the immediate and underlying causes of malnutrition including population prevalence of key diseases, food security and dietary intake. Survey data for the period February to April 2020 was available for the six selected districts of the Greater South. For three of the six districts, existing data collected just prior to the lockdown was available from a national survey on women’s nutrition and vitamin A coverage from February to March 2020. This data was re-analysed to calculate GAM rates. Data for the remaining three districts was directly available.
Data was projected for May to August 2020 and September to December 2020 based on IPC guidelines (IPC, 2019) using historical data on outcome indicators and trend data on contributing factors derived from the national health management information system (HMIS) and other sources. All projections were informed by assumptions based on the IPC GSU guidance note on developing assumptions for projection analysis in the context of COVID-19 (IPC, 2020a). Other indicators were drawn from district-level surveys, food security assessment reports, disease trends provided by the Demographic and Health Information Software II (DHIS2), coverage survey reports, SMART surveys and Link Nutrition Causal Analysis (Link NCA) surveys conducted over the last three years.
The likely impact of COVID-19 on acute malnutrition was also considered, drawing from IPC GUS technical guidance (IPC, 2020b). Pathways for impact were explored including the likely negative impact on food systems and access to health services in the post-harvest period. The tools, data and indicators were subsequently made available online for the working groups during the analysis.
Composition of analysis team
The virtual IPC-AMN analysis team included 23 participants, comprising 18 locally based partners3 and five external IPC experts including four Cross Country Learning Exchange (CCLE) participants (from the Ministries of Health in Burkina Faso and Niger, UNICEF West and Central Africa Office (WCARO) and CILSS4) and an IPC-GSU focal person based in Rome. The 18 locally based participants formed the group that usually participated in IPC-analyses in-country, however there was more external participation (CCLE participants) in this analysis to support the virtual methodology used. The four CCLE participants shared their experiences on nutrition indicators and virtual analysis and learned from Madagascar’s experience. Commitment was given from each of the member organisations to fully attend the entire virtual process.
At the start of the virtual sessions, participants were assigned to one of six working groups each focusing on one of the districts, ensuring a spread of technical expertise and organisational affiliation. Each working group was led by a focal person from a different organisation including Action Contre la Faim (ACF), CARE International, the Food and Agriculture Organization (FAO), MoH, the National Nutrition Office under the Prime Minister’s Office (ONN), the National Office of Disaster and Risk Management (BNGRC) and UNICEF. A local country facilitation team was comprised of three experts to oversee the working groups which were comprised of national experts experienced in IPC methodology with extensive knowledge of the local context (from BNGRC, MoH and UNICEF). The IPC-GSU also provided two facilitators from its pool of global and regional experts. At different stages of the analysis, focal persons from each of the six districts were consulted for knowledge of the local context. Support to district-level participants in the form of data bundles was provided to facilitate internet access and participation in online sessions.
Stage three: analysis
Under normal circumstances, IPC analysis is conducted with a group of three to four persons per district (or unit of analysis). Groups usually travel to one location for the analysis and remain together for the duration of the training and analysis. There is a designated facilitator for each group to assist with technical questions, monitor the progress and act as spokesperson to IPC technical leads and documents are shared via USB flash drives. For the virtual process, a similar process was used but working group sessions were conducted virtually (using Skype and Zoom), administered by BNGRC (supported by the provision of data bundles for each participant) and files were shared using Dropbox. The MoH provided participants with full online access to the country’s HMIS and nutrition-related indicators. UNICEF and the IPC-GSU focal person, as technical leads, created and sent out calendar invitations to participants and meeting reminders 30 minutes prior to each session.
Box 1: ICP-AMN analysis steps
The participants of each working group spent about three to four hours in working sessions on Skype each day. Working groups made their own arrangements with their group facilitator on how to complete assigned activities which typically included two to three IPC-AMN steps per day out of the total eleven IPC-AMN analysis steps (Box 1). The most common arrangement was that participants took turns to take breaks when needed while the other participants continued to work.
There was a one-hour lunch break every day followed by a Zoom plenary session for all the working groups, during which the group’s designated rapporteur presented on the working groups’ deliberations and conclusions for validation within the wider group.
Stage four: Wrap-up
The results of all the group analysis per district were validated in plenary sessions after which they were presented to the national Nutrition Cluster by the chair of the country IPC-TWG for clearance. This was a similar process to a typical IPC analysis, although validation took place online. The analysis team finalised the IPC report according to IPC guidelines and this was then presented virtually to the cluster after which comments and feedback were integrated into the report before submission to the IPC-GSU for review. The final version was then officially released by BNRGC.
The results of the Madagascar IPC-AMN analysis estimated GAM prevalence to be between 10.5-16.8%, severe acute malnutrition (SAM) prevalence was estimated to be between 1.6-3.7% and moderate acute malnutrition (MAM) was calculated to be between 9.0-14.4%.5 Based on these estimates, it was calculated that 119,674 children 6-59 months of age would need treatment for acute malnutrition between February and December 2020 (Figure 2). Out of these, 16% would need treatment for SAM.
Figure 2: IPC-AMN Madagascar key results, June 2020
Results estimated that the nutrition situation would likely deteriorate in all six districts beyond August 2020 due to the agricultural lean season and the effects of COVID-19 (Figure 3). Such factors were expected to result in a slight deterioration in four districts (Toliary-II, Ampanihy, Beloha and Tolagnaro) without changing their global classification of IPC Phase 3 – ‘serious’. However, results estimated that Betioky district would likely move into the serious phase category (IPC Phase 3) and Ambovombe district into the ‘critical’ phase (IPC Phase 4) requiring special attention and an urgent and targeted response. Full results are provided in the report.6
Figure 3: IPC AMN Results Maps.
The full report can be accessed on the IPC website here.
Key success factors
The IPC-AMN team in Madagascar leveraged existing local opportunities and prevailing political will to organise a virtual IPC-AMN analysis, the first remote IPC acute malnutrition analysis conducted globally. Key success factors were a dynamic and motivated country team, openness, the willingness and participation of national and district level representatives of three key government institutions (the National Nutrition Office, the BNGRC and the MoH) and full sharing of the national HMIS platform. In addition, the IPC team enjoyed a healthy working relationship with the food security, social protection, WASH and health clusters which enabled the sharing of important contextual information. Another key factor was the technical support provided by the IPC GSU and IPC CCLE participants who were able to participate remotely from Niger, Burkina Faso and Rome. Overall, the use of virtual meeting methods enabled the participation of a high calibre of local and international experts that allowed a high-quality process in line with IPC guidelines.
Data collected via a national nutrition survey just prior to the lockdown that included anthropometric data was available and helped form a reliable basis for the baseline IPC projections. While the nutrition assessment was not directly representative of each unit of analysis, it was possible to re-calculate nutrition outcomes per unit of analysis informed by IPC-GUS guidance. This was important as it allowed for the use of recently collected, existing data to ensure a robust and credible analysis. Projections from this analysis have proved to be accurate, as Southern Madagascar is now facing great increases in levels of child wasting across the region.7
Organising an IPC-AMN analysis exercise without up-to-date nutrition survey data seemed, at first, to be a daunting task and required additional work to recalculate available data. The fact that recent data was only available for three districts was problematic and required strong statistical capacity within the country core team to perform appropriate recalculations of all nutrition indicators at district level before the data could be integrated into the analysis. The most recent IPC Technical Manual supported this process.
As this was the first remote IPC-AMN analysis conducted during the pandemic, there were no existing global guidelines to support remote facilitation; the in-country team therefore had to develop their own ways of working. The team faced difficulties coordinating the facilitation of plenary sessions and supervising working groups in a way that would ensure rich discussion and debate between participants. As noted previously, keeping participants engaged and committed for many hours per day was not easy. To overcome this, plenary sessions were limited to just one hour a day and the process was kept to no longer than five hours per day. These challenges were further overcome by ensuring an adequate number of experienced IPC facilitators. Internet connectivity was a notable challenge throughout which, at times, led to reduced engagement by district-level participants. This was addressed by providing internet bundles to participants which to some extent helped to overcome the issue.
Another challenge was that, at the time of planning the IPC-AMN analysis, there was a limited understanding of the potential impact of COVID-19 on malnutrition estimates and a lack of clarity on how to develop appropriate hypotheses. This was overcome through technical guidance provided by the IPC-GSU focal point, drawing from the latest IPC technical guidance, although there remained many unknowns due to the evolving nature of the pandemic.
This experience has provided rich learning. Specific lessons learnt include the following:
- Planning and preparation of a virtual IPC analysis requires sufficient time – at least seven days prior to the intended start date. This is more than is typical during a face-to-face analysis and is required to ensure the availability of as much necessary data and information as possible for the working groups to enable them to carry out the analysis in a shorter time frame.
- It is possible, despite the challenges, to use existing available data with re-analysis to the relevant level of unit of analysis. This process, however, requires a high level of technical support for the statistical analysis and additional time to recalculate nutrition indicators.
- The use of team members previously trained in IPC analysis saves time and ensures quality input for the analysis. If this is not possible, an online training could be carried out to build the capacity of less experienced participants prior to the analysis, however, this would considerably lengthen the time taken for necessary online engagement which should be taken into account.
- Optimising the capabilities of video-conferencing solutions for working group interactions, discussions and plenary presentations kept participants engaged throughout the exercise.
- If there is poor internet connectivity, a virtual IPC analysis may lead to decreased participation of key authorities and partners at decentralised levels. It is, however, vital to include district level participants to ensure inclusion of deeper insights and knowledge of the areas under analysis. Provision of adequate internet bundles can help to support participation of all partners.
- High quality online facilitation is needed to ensure good participation from all group members, in particular ensuring that every participant has a chance to contribute. For this, the use of all the features of the online tools was helpful including screen sharing and the use of breakout rooms with facilitators moving between rooms.
The lessons learnt through this exercise have shown that, with good levels of supervision and with support to facilitate internet connectivity, it is possible to carry out high-quality IPC-AMN analyses remotely in the context of Madagascar. Adapting to carry out this process remotely was critical to ensure the continuity of IPC-AMN analyses in the context of a national lockdown prompted by COVID-19. The results accurately predicted a decline in the nutrition situation and informed a national-level nutrition response. The results of the initial virtual IPC-AMN analysis were presented at UNICEF's East and Southern Africa regional meeting in June 2020 as a successful example of continuity of activities despite COVID-19 for other countries to learn from and replicate. Since this presentation, another online exercise was carried out in November 2020 in Madagascar and the experience was also replicated in Uganda, Chad, Kenya, Somalia, Burundi and Yemen.
2 This follows the normal historical process for conducting IPCs in Madagascar but was held online, and therefore the duration was shorter and there was no in-person training.
3 These 18 participants included 10 ten nutrition and health focal points from districts level government, central MoH and Action Contre la Faim (ACF), four food security focal points from FAO, WFP, three wash and social protection focal points from ACF and CARE International and one disaster risk management focal point.
4 CILSS = le Comité permanent inter-États de lutte contre la sécheresse dans le Sahel (Permanent Inter-state Committee for drought control in the Sahel)
5 Note this is a combined prevalence estimate, i.e., according to weight for height and/or mid-upper arm circumference and/or oedema presence anthropometric indicators.
IPC Global Partners (2019) Integrated Food Security Phase Classification Technical Manual Version 3.0. Evidence and Standards for Better Food Security and Nutrition Decisions. Rome. http://www.ipcinfo.org/fileadmin/user_upload/ipcinfo/manual/IPC_Technical_Manual_3_Final.pdf
IPC (2020a) COVID-19 IPC Technical Guidance Note. Rome. http://www.ipcinfo.org/fileadmin/user_upload/ipcinfo/docs/documents/IPC_Technical_-Guidance_to_Build_AMN_Assumptions_in_Covid19_Context.pdf
IPC (2020b) Madagascar: Acute Malnutrition Situation February - April 2020 and Projections for May - August 2020 and September - December 2020: http://www.ipcinfo.org/ipc-country-analysis/details-map/en/c/1152677/?iso3=MDG
UNICEF (2013) Improving Child Nutrition: The achievable imperative for global progress. United Nations Children’s Fund; 2013. p. 4 (https://www.unicef.org/media/files/nutrition_report_2013.pdf )
UNICEF (2018) Enquête nationale sur la situation socio-démographique des ménages (MICS), Madagascar. https://mics.unicef.org/surveys
More like this
FEX: Réalisation à distance du cadre intégré de classification de la sécurité alimentaire durant la pandémie de COVID-19 : l’expérience de Madagascar
Read an English version of this article here Par Smaila Gnegne, Moussa Moctar, Andrianianja Raonivelo, Desire Rwodzi, Mara Nyawo et Douglas Jayakasekaran Smaila Gnegne est...
FEX: Calculating wasting caseloads and geographic prioritisation of nutrition services in the context of limited data in Afghanistan
View this article as a pdf By Beka Teshome Bongassie, Said M Yaqoob Azimi and Maureen L. Gallagher Beka Teshome is Nutrition Cluster co-lead for Afghanistan with Action...
FEX: A risk communication and community engagement (RCCE) response to support maternal, infant and young child nutrition in the context of COVID-19 in Rwanda
View this article as a pdf By Annet Birungi, Ken Limwame, Desire Rwodzi and Youssouf Koita Annet Birungi is an experienced Communication for Development Specialist at UNICEF...
View this article as a pdf By Getinet Babu, Agnes Aongola, Colleen Emary, Phyllis Oyugi, Claire Beck, Chansa Tembo Getinet Babu is a humanitarian nutritionist with over 16...
View this article as a pdf By Sahra Moalim Ahmed, Bishar Osman Hussein and Emmanuel Barasa Sahra Moalim Ahmed is an Infant and Young Child Feeding Officerat Concern Worldwide...
View this article as a pdf Dear readers, A warm welcome to the 65th edition of Field Exchange. This edition features a range of programming issues that unfortunately reflect...
This is a summary of a Field Exchange field article that was included in issue 64. The original article was authored by Getinet Babu, Agnes Aongola, Colleen Emary, Phyllis...
FEX: Concordance between weight-for-height z-score (WHZ) and mid-upper arm circumference (MUAC) for the detection of wasting among children in Bangladesh host communities
View this article as a pdf Lisez cet article en français ici By Md. Lalan Miah, Dr. Md. Khalilur Rahman, Dr. Md. Abdul Alim and Bijoy Sarker Md. Lalan Miah is the...
View this article as a pdf By Md. Lalan Miah, Bijoy Sarker, Jogie Abucejo Agbogan, Brigitte Tonon, Mary Chelang'at Koech and Md. Shahin Emtazur Rahman Md. Lalan Miah is...
FEX: Use of RapidPro for remote collection of nutrition data during the drought emergency and COVID-19 pandemic in Zimbabwe
View this article as a pdf By Nakai Munikwa, Pauline Tsikayi, Desire Rwodzi, Mara Nyawo and Mathieu Joyeux Nakai Munikwa is the Nutrition Cluster's Information Management...
View this article as a pdf Lisez cet article en français ici By Maria Wrabel, Sarah King and Heather Stobaugh Maria Wrabel is CMAM Adaptations Project Officer with...
View this article as a pdf Lisez cet article en français ici By Saidou Magagi, Sumra Kureishy, Jessica Bourdaire and Katrien Ghoos Saidou Magagi is a monitoring,...
FEX: Use of RapidPro for remote collection of nutrition data during the drought emergency and COVID-19 pandemic in Zimbabwe
This is a summary of a Field Exchange field article that was included in issue 64. The original article was authored by Nakai Munikwa, Pauline Tsikayi, Desire Rwodzi, Mara...
FEX: Integrating screening for acute malnutrition into the vitamin A supplementation campaign in the Rohingya camps during the COVID-19 pandemic
View this article as a pdf Lisez cet article en français ici By Bakhodir Rahimov, Karanveer Singh and Piyali Mustaphi Bakhodir Rahimov is a Nutrition Sector...
View this article as a pdf Lisez cet article en français ici By Tracy Dube, Mary Chelang'at Koech, Piyali Mustaphi, Sandra Harlass, Jessica Bourdaire and Karanveer...
FEX: Streamlining SMART survey processes in support of a high quality, nationally owned nutrition information system in Kenya
View this article as a pdf Lisez cet article en français ici By Lydia Ndung'u, Lucy Maina-Gathigi, Lucy Kinyua, Hassan Ali Ahmed, Kibet Chirchir and Samuel Mahinda...
Moringa is a nutritious tree grown in the tropics, sometimes called the ‘miracle tree’. Does anyone have any good programming examples that they can share with us at Save the...
FEX: Improving nutritional outcomes of rural households through a community-based approach in Ethiopia
This article has been updated since the original version was published in March 2020. View this article as a pdf Lisez cet article en français ici By Haimanot Abebe,...
en-net: WEBINAR - SAFELY RESUMING DOOR-TO-DOOR SURVEYS: DATA COLLECTION AND UTILIZATION IN THE CONTEXT OF COVID-19
Tech RRT in collaboration with SMART, GNC, GNC-Technical Alliance (formerly GTAM), IPC, UNICEF and Save the Children invites you to a new webinar to support nutritional surveys...
By Anna Ziolkovska View this article as a pdf Lisez cet article en français ici Anna Ziolkovska is currently the Nutrition Cluster Coordinator in Yemen. Anna has a...
Reference this page
Smaila Gnegne, Moussa Moctar, Andrianianja Raonivelo, Desire Rwodzi, Mara Nyawo and Douglas Jayakasekaran (). Remote Integrated Phase Classification during the COVID-19 pandemic: experiences from Madagascar. Field Exchange 65, May 2021. p42. www.ennonline.net/fex/65/virtualipcmadagascar