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RBM-HWG Needs Assessment Calculation Tool User Guide General remarks Principal approach to estimations and output Data entry sections 1. Demography 2. Endemicity Malaria rates in <5 % reduction high low 0 2.50 1.00 10 2.25 0.90 20 2.00 0.80 30 1.75 0.70 3. Health Services 4. Prevention 5. Treatment Troubleshooting Acknowledgement RBM-HWG Needs Assessment Calculation Tool User Guide This tool was developed for consultants involved in the Roll Back Malaria Harmonization Working Group Needs Assessment to assist in the primary objective, i.e. to assess whether or not a country's current planning and resources are sufficient to reach and sustain the 2010 RBM and country specific targets and if not what is the order of magnitude of required inputs. It is not meant nor able to replace detailed costing of activities as needed for implementation plans and budgets. In order to be generally applicable to countries in sub-Sahara Africa as well as easy to use some common assumptions are necessary and results should be seen as approximate figures. General remarks The tool has one principal data input page although some selection of options are also possible on the ITN and IRS output page. The major output tables provide annual need and cost for the major commodities for treatment and prevention of malaria. Additional pages provide data and graphs on the estimated number of fever cases, 1st line treatments, malaria cases etc as well as the population at risk for malaria by various age groups The file is "read only" and in order to save any country settings it must be saved under a new name. No changes can be made by the user on the output pages but you can copy/paste the information into a new spreadsheet (best use paste-special> values and number formats only) for further use. Two options exist if you want to reset the values of the data entry page: you can either press the "reset" button on the top of the page (macros must be enabled). This will return the input to the default settings except for those fields with pull-down menues or select boxes. Or you just close the file without saving and re-open. This way all fields including pull-down menues and selection boxes will be reset. Principal approach to estimations and output This section briefly summarizes the approach that has been used for the estimations. More detailed notes regarding the used assumptions for the ITN and treatment need calculations are given on the "Notes" page at the end. Starting point for all calculations is the population estimated for each year based on country data (population and growth rate) stored in the sheet or provided by the user. The population is then "split" into different age groups and target groups such as pregnant women. Source for the preset country data are given at the bottom of the "Population" page. The mosquito net section only deals with ITNs and ignores untreated nets. Assuming that in the future only LLINs will be used in public sector distributions no scenarios for re-treatment campaigns have been included since - if targets for 2010 are met - the vast majority of nets will be LLIN and the number of untreated nets negligible. If a country is planning such a campaign they have to be calculated separately. The starting point of calculations for the LLIN needs to achieve RBM target is the net crop (number of nets) at the end of 2007 which is calculated from past survey data supplemented by an estimate of the input since the survey or by an "informed guess" by the consultants for the 2007 situation. Percent coverage with ITN is converted to number of nets based on the number households and the mean number of nets per household derived from empirical data (see Notes). Nets are lost over time at rates that are based on detailed loss estimates for different net types assuming a mix of polyethylene and polyester nets (see Notes). Two major outputs are provided to allow a judgement whether or not targets are likely to be reached: 1. An estimate of the LLIN needed to reach the 2010 target of either 80% or 100% of households with sufficient nets (number of nets per households varies with size of households) and then sustain that level to 2013. A range of values is given where the low value assumes that previously distributed nets (not yet lost) are considered while the high estimate ignores them (for 2010) or uses only 50% of them (2013). The targets refer to all households. If a country target is only defined as "households with a child under 5 or pregnant woman" this lower target can only be estimated by reducing the "proportion targeted for ITN" (F45). 2. A calculation of LLINs to be distributed based on planned activities (campaign and different types of routine distributions). These can be varied by year and approach separately for the period 2008-2010 and 2011-2013 on the ITN output page. Please note that these are two totally independent calculations. The first calculates backwards from the households in 2010 and 2013 respectively how many nets will have to be distributed in the previous years to cover 80% or 100% of households with the number of nets associated with these coverage levels (see Notes for the exact figure) and makes some assumptions about loss of nets in the previous years. The second is based only on the population figures and calculates how many nets are needed if each child under 5, each woman attending ANC at least once etc. is to be given a net in a given year. This then allows an assessment whether the planned distribution activities will be sufficient to reach the targets or whether additional activities (e.g. doing a general campaign rather than only to under 5s) should be recommended. Calculation of fever and malaria cases, treatment needs and diagnostics is a special challenge as most variables such as proportion with access to health services, choice of provider, compliance with treatment guidelines etc will change over time. To take this dynamic into account is clearly beyond this tool and must be done in more complex models. However, the tool is able to give a reasonable estimate of the number first line ACTs and RDTs needed in the next 3 years. It is probably less accurate for the 2011-2013 period if the real situations deviates significantly from the assumption made in the calculation. Need for second line drug and severe malaria cases have not been included. The major reason is that most of the factors that drive these cost are either not constant over time or poorly understood (e.g. severe cases in a situation with decreasing transmission). In addition their cost is marginal compared to first line ACT and RDTs and. In most cases a 5% cost compared to first line is a reasonable estimate. Also, no cost for microscopy have been calculated as these are part of the health system cost that have to be estimated separately. From recent data it is evident that consequent implementation of malaria prevention and treatment will lead to dramatic reductions in actual malaria cases. This will lead to reductions in the "true" malaria cases but only translates into savings for ACTs if the number of diagnostic tests is dramatically increased. In order to allow calculation of such reduced need for ACTs the calculations assume that the RBM targets actually will be met and therefore apply a reduction of maraia incidence of 25% by 2010, 75% by 2011 and 80% thereafter. Further details of assumptions for fever episodes per person per year are given in the Notes. Data entry sections The data entry page is structured into 5 sections. All these must be carefully filled before any useful output can be obtained. Most fields where country specific information is needed are set to 0 as default. In some cases, however, some commonly used values have been entered. If better information is available in country these should be overwritten. Some comments and clarifications for input needs are given directly on the input page. Below are some additional points for specific sections: 1. Demography The easiest way is to load the country data set from the pull down menu. The figures may vary from what the country uses as most population fugures are based on census data many years old. Population figures can be entered manually but it should be kept in mind that differences of a few %-points up and down (or decimal points for rates) hardly make a difference in the outcome given the rather rough assumptions that have to be made. Since at the time of the development of this tool the list of countries for needs assessments was still changing not all countries have preset data. 2. Endemicity This section is crucial for the results. It first allows the definition of that part of the population that is living in areas with no malaria risk. This part of the population will then be excluded from all calculations. In the next step the proportion of the total population in areas of two different levels of endemicity needs to be defined. These two settings are "high to very high" and "medium to low". In many countries the terms "high" and "low" are used with very differing underlying actual transmission and may only refer to the relative level within the country. For these calculation a high level of endemicity means on average 2.5 malaria episodes per child under 5 per year at baseline and 0.8 episodes for persons 5 years and older. The rates for "low" areas are 1.0 and 0.4 respectively.Therefore, some areas that are considered "high" by NMCP relative to the country may actually be "low"last these in this section can provide an estimate of what level of malaria reduction has been achieved The by entry standards. already. This is meant to allow an initial reduction of malaria cases from the "intrinsic" endemicity in countries where high levels of ITN coverage or ACT treatments have been reached. The maximum level allowed is 30%.However, this variable (F 27 in data input) can also be used to modify the baseline settings of the malaria incidence for "high" and "low" endemicity areas as follows: Malaria rates in <5 % reduction high low 0 2.50 1.00 10 2.25 0.90 20 2.00 0.80 30 1.75 0.70 3. Health Services There are two entries for "access" to health services. One for the reach of public health services in general (but should include outreach activities and will in some countries also include NGO-run facilities). The other refers to treatment access in children. This is needed to allow for a scenario where community based treatment is implemented and hence access to public treatment is higher for under5s than for the general population. If no home-based management of malria (HMM) is planned, the two rates should be the same. Those not accessing the public sector are then automatically defined as "private sector". ANC attendance figures can usually be obtained from the most recent DHS, MICS or MIS. 4. Prevention The first and most important step is to define that part of the population at risk of malaria that is targeted for ITNs and IRS. It should be noted that the targets for ITN and IRS are independent so that a simultaneous coverage of both ITN and IRS can be included. A clarification on different campaigns: a "general" campaign is any time of limited distribution (integrated or stand alone) that is not giving nets to children under five and/or pregnant women. Calculations for these general campaigns are based on the households and the number of nets given (on average) per household. In contrast, the under five and pregnant women campaigns are calculated based on the estimated population of these categories. As explained in the previous section the ITN output table regarding the need to achieve targets by 2010 and 2013 respectively (left top) is independent from the number of nets needed for specific delivery approaches but both relate to (and therefore are modified by) the proportion of the population targeted for ITN defined in field F45. The routine distribution figures are also influenced by the health service settings (proportion attending health services and ANC). Field F60 allows an additional modification (i.e. reduction of nets) but only applies to general campaigns. It is meant to adjust for situations where not every household within the population targeted for ITN will receive the specified number of nets defined in F59. It is recommended to use this feature cautiously and generally leave it at 100% if a "universal access" campaign is planned. However, it can be used if certain geographically limited campaigns (i.e. not covering the whole population who are in principal targeted for ITN) are planned or if the campaign only plans to cover certain households (e.g. any household with children under 10 receives x nets). Table 12 of the report template requests the number of LLIN delivered by delivery approach. These are obtained from the two lower tables on the ITN output page (for campaign choose the respective year). They can be added up in the table on the top right of that page according to country plans using the pull-down menus and be compared with the "needs estimates". The resulting number of nets may exceed the target estimates if e.g. a campaign is undertaken where every child under 5 receives a net irrespective of whether the household already has a net or not. However, the resulting number from the top right table should not be significantly below the estimate or the delivery strategy must be adjusted (one exception may be that significant input is also expected from the commercial sector which is not considered in this tool). The cost of the nets entered in field F61 is meant to cover the cost of the commodity (CIF) but not delivery to the recipient. The reason for this is that delivery cost may differ significantly by delivery mechanism. However, Table 12 in the report template requests the average cost per LLIN delivered by delivery mechanism. This can be obtained either by adding the cost for delivery manually or by modifying the cost in the data input page (F61). In the latter case care must be taken that only figures of needed LLIN for that particular delivery approach to which the modified cost applies are copied. 5. Treatment For the calculation of IPT the proportion of population covered with this intervention has first to be entered. This is necessary as in some countries the IPT area is not identical with the total area at risk. Note that the proportion here refers to the total population, not the population at risk. Next the proportion of non-falciparum malaria among malaria cases has to be entered. This is meant to allow a separate calculation for vivax/ovale cases where these are significant and are not treated with an ACT. Note, however, that this rate should refer only to mono-infections as mixed infections have to be treated with ACTs. In most cases this rate should be set to 0%. The ACT regimens differ in age/weight cut-off between AL and other ACTs. Selecting the 1st line ACT in the box will then bring up the corresponding age categories. The diagnostic section is very important as it will determine the need for ACTs in the future. Since in most countries the situation outlined in the policy or planned for implementation is not yet achieved, a current (2008) as well as future scenario is allowed. Calculations will then assume that 2009 will be a transition year and full scenario reached in 2010. The figures needed to fill Table 17 of the report template then can be obtained from the ACT & RDT output page. Additional information is also provided on the "cases" page which has two sections, the upper table presents figures for the total population at risk while the lower lable shows only the figures for the public sector. The two graphs are based on these two tables. Troubleshooting The tool has been test run to ensure that all calculations and options work properly. However, some bug or error cannot be excluded (this is version 1.2!). Nonetheless, if you encounter some "weird" results please first carefully check your data entry and ensure that all are what you wanted them to be as this is the most likely cause. If you encounter unsolvable problems, need a "special solution" or simply have suggestions for improvements in the future please contact Albert Kilian at <a.kilian@malariaconsortium.org>. Acknowledgement While most of the calculations are based on previous work done in Uganda for the GFATM proposals it builds on significant inputs also from Elizabeth Streat (Malaria Consortium) and Bruno Moonen (Clinton Foundation). RBM-HWG Needs Assessment Calculation Tool Data entry areas and variables 1. Demographic data Select country profile other Entered data Preset estimates Year Year 2007 Population Population 0 Annual growth (%) Annual growth 2.5% Persons/household Persons/household 5.0 % age 0-4 % age 0-4 16.5% % pregnant women % pregnant women 4.5% 2. Malaria endemicity Proportion of population not at risk of malaria (%) 0.0% Proportion of population at high to very high risk of malaria (%) 0.0% Proportion of population at medium to low risk of malaria (%) 100.0% Current level of malaria reduction (%) 0.0% 3. Health services Population with access to public health services (%) 0.0% Fever cases in under 5s treated in public sector (%) 0.0% Proportion of women attending ANC at least once (%) 0.0% Proportion of women attending ANC at least twice (%) 0.0% 4. Prevention NMCP targets for 2010 for malarious areas Proportion of at risk population targeted for ITN (%) 0.0% Proportion of at risk population targeted for IRS (%) 0.0% ITN FALSE Survey data (2005 or later) available Year of last national survey At least ITN must be filled! Proportion of households with at least one net (%) 0.0% Proportion of households with at least one ITN (%) 0.0% Proportion of households with at least one LLIN (%) 0.0% Total number of ITN/LLIN distributed since survey Number of nets calculated per household for general campaign 2 Proportion of targeted population reached by general campaign 100.0% Cost per LLIN in $ $6.00 IRS Proportion of households to be covered within targeted area (%) 0.0% Average # of structures to be sprayed per household 2 Proportion of structures "formal" 0.0% Average surface for formal structure in m² 200 Average surface for informal structure in m² 90 Number of spray rounds per year 1 Average cost per household sprayed in $ $8.00 5. Treatment and diagnosis IPT Proportion of population where IPT is implemented 0.0% Price per tin (1,000 tabs) of SP in $ $24.00 Treatment & diagnosis Proportion malaria cases being non-falciparum (%) 0.0% Average treatment cost per case of non-falciparum malaria in $ $0.10 First line ACT Artemether/Lumefantrine 1 Other ACT e.g. AS+SP or AS+AQ Cost of 1st line ACT per dose in $ Age groups in years <3 $0.90 3-8 $1.00 9-14 $1.20 15+ $1.80 Proportion of all fever cases in public sector to be diagnosed current children under 5 yrs planned 0% Microscopy 0% 0% RDT 0% 0% Total proportion of under 5 diagnosed 0% current 5 yrs and above planned 0% Microscopy 0% 0% RDT 0% 0% Total proportion of 5 and older diagnosed 0% Estimated proportion diagnosed in the private sector current planned 0% Microscopy 0% 0% RDT 0% 0% Total proportion diagnosed 0% Cost for RDT in $ $0.80 Comments Select the preloaded country data and change only if they significantly deviate from estimate normally used 0 0 If you choose to enter different data you must fill at least the first 2 fields This part of the population will not be included in the calculations Please carefully read user guide before filling in! This field is calculated from the previous two See user guide for explanations how to use this field Including outreach activities Including HMM, should be the same as total population if no HMM Excludes the population not at risk ITN and IRS areas may overlap If data from 2005 or later available tick box and enter year Mention the type of survey (DHS, MIS, MICS) in the report If no recent survey data leave blank must be filled! If no recent survey use "informed guess" for 2007 If no exact data use "informed guess" This rate does not apply to other campaigns (children under 5 & PW) Basic unit cost should be CIF and not delivery to recipient. Delivery cost must be calculated separately. (see also user guide) formal =non-porous surface, i.e. any structure with four walls and a roof with smooth, not absorbant plaster or painted wall informal =porous surface, i.e. any structure with four walls and a roof with porus walls (e.g. unfinished brick, cement block, reeds, stone, mud plastered or earth) Include non-insecticide commodity, training cost and implementation cost Proportion refers to total population of country! In order to allow exclusion of IPT in low malarious areas refers to natinal average and only non-pf mono-infections! Age groups are proxies for weight categories which may vary <3 slightly between countries 3-8 9-14 15+ <1 1-6 See explanation in user guide 7-13 14+ Informed guess If no estimate possible all cases will be treated clinically other Burkina Faso Burundi Cameroon CAR Comoros Congo Cote d'Ivoire DRC Eq. Guinea Ethiopia Gabon Ghana Kenya Mali Mozambique Nigeria Tanzania Togo Zanzibar Zimbabwe Prevention with Insecticde Treated Nets (LLIN) Approximate need for LLIN to reach and maintain 2010 targets for population at risk targetd for ITN Planned distributio Time period 2008-2010 2011-2013 Target 80% 100% 80% 100% LLIN low estimate 0 0 0 0 high estimate 0 0 0 0 LLIN mean 0 0 0 0 Routine Cost Campaign low estimate $0 $0 $0 $0 Total high estimate $0 $0 $0 $0 Cost mean $0 $0 $0 $0 Total Estimated annual need for routine LLIN distribution in various scenarios for populations at risk targeted for ITN 2008 2009 2010 2011 2012 2013 LLIN ANC 0 0 0 0 0 0 EPI 0 0 0 0 0 0 ANC & EPI 0 0 0 0 0 0 None Cost ANC $0 $0 $0 $0 $0 $0 EPI $0 $0 $0 $0 $0 $0 ANC & EPI $0 $0 $0 $0 $0 $0 Approximate need for campaign LLIN in a given year in various scenarios for populations at risk targeted for ITN 2008 2009 2010 2011 2012 2013 LLIN Under 5 0 0 0 0 0 0 Under 5 & PW 0 0 0 0 0 0 General 0 0 0 0 0 0 None Cost Under 5 $0 $0 $0 $0 $0 $0 Under 5 & PW $0 $0 $0 $0 $0 $0 General $0 $0 $0 $0 $0 $0 Planned distribution activities ANC select campaign year EPI None None select campaign type ANC & EPI None None select type of routine distribution None Time period 2008-10 2011-13 Under 5 0 0 Under 5 & PW 0 0 General 0 0 None $0 $0 Period 2008-10 2011-13 0 0 0 0 0 0 $0 $0 $0 $0 $0 $0 Period 2008-10 2011-13 0 0 0 0 0 0 $0 $0 $0 $0 $0 $0 Indoor Residual Spraying 0% population targeted with IRS 0% Annual targets and approximate cost for Indoor Residual Spraying 2008 2009 2010 2011 Households targeted 0 0 0 0 Population covered 0 0 0 0 Formal structures to spray 0 0 0 0 Informal structures to spray 0 0 0 0 Approximate cost $0 $0 $0 $0 Some insecticides commonly used for IRS Insecticide Brand Formulation dose (mg/m²) gram/sachet DDT 75% 2,000 670 Lambda-cyhalothrin ICON 10% 25 62.5 Alpha-cypermethrin Fendona 5% 25 125 Deltamethrin K-Othrine 5% 25 80 Bendiocarb 80% 400 125 Insecticide calculator Number of sachets of selected insecticide needed Structure Selected Insecticide 2008 2009 2010 2011 Formal Lambda-cyhalothrin 0 0 0 0 Informal Lambda-cyhalothrin 0 0 0 0 targeted households within IRS area ual Spraying 2012 2013 0 0 0 0 0 0 0 0 $0 $0 m²/sachet 251.25 DDT 250.00 Lambda-cyhalothrin 250.00 Alpha-cypermethrin 160.00 Deltamethrin 250.00 Bendiocarb d insecticide needed 2012 2013 0 0 0 0 Intermittent Preventive Treatment in Pregnancy 0.0% of total population targeted for IPT Number of women targeted for IPT 2008 2009 2010 Women currently attending ANC 0 0 0 Women currently attending ANC at least twice 0 0 0 80% of all pregnant women 0 0 0 100% of pregnant women 0 0 0 Annual SP treatments (2 doses per woman) 2008 2009 2010 Women currently attending ANC 0 0 0 Women currently attending ANC at least twice 0 0 0 80% of all pregnant women 0 0 0 100% of pregnant women 0 0 0 Approximate need for SP* 2008 2009 2010 Tins of 1,000 tabs Women currently attending ANC 0 0 0 Women currently attending ANC at least twice 0 0 0 80% of all pregnant women 0 0 0 100% of pregnant women 0 0 0 Cost in $ Women currently attending ANC $0 $0 $0 Women currently attending ANC at least twice $0 $0 $0 80% of all pregnant women $0 $0 $0 100% of pregnant women $0 $0 $0 * adding 15% for women receiving more than 2 doses and 10% for logistic add-on opulation targeted for IPT 2011 2012 2013 0 0 0 0 0 0 0 0 0 0 0 0 2011 2012 2013 0 0 0 0 0 0 0 0 0 0 0 0 2011 2012 2013 0 0 0 0 0 0 0 0 0 0 0 0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 Treatment & Diagnostics Needed treatments for 1st line ACT, non-falcuparum m in public sector ACT 2008 2009 2010 P. falciparum malaria Age group in yrs <3 #DIV/0! #DIV/0! #DIV/0! 3-8 #DIV/0! #DIV/0! #DIV/0! 9-14 #DIV/0! #DIV/0! #DIV/0! 15+ #DIV/0! #DIV/0! #DIV/0! Total #DIV/0! #DIV/0! #DIV/0! Cost for ACT in $ #DIV/0! #DIV/0! #DIV/0! Non-falciparum malaria # of non-falciparum treatments #DIV/0! #DIV/0! #DIV/0! Cost for non-falciparum in $ #DIV/0! #DIV/0! #DIV/0! Diagnostics # of microscopy tests 0 0 0 # of RDTs 0 0 0 Cost of RDT in $ $0 $0 $0 e ACT, non-falcuparum malaria and diagnostic tests in public sector 2011 2012 2013 #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! 0 0 0 0 0 0 $0 $0 $0 Cases, diagnosis and treatments Total population Age group 2008 2009 under 5 yrs 0 0 Fever cases 5 yrs & above 0 0 Total 0 0 under 5 yrs 0 0 Diagnostic tests 5 yrs & above 0 0 (micro or RDT) Total 0 0 under 5 yrs #DIV/0! #DIV/0! % fever cases diagnosed 5 yrs & above #DIV/0! #DIV/0! (micro or RDT) Total #DIV/0! #DIV/0! under 5 yrs #DIV/0! #DIV/0! Cases treated with ACT 5 yrs & above #DIV/0! #DIV/0! Total #DIV/0! #DIV/0! under 5 yrs 0 0 True malaria cases 5 yrs & above 0 0 Total 0 0 under 5 yrs 0 0 True malaria cases 5 yrs & above 0 0 (P. falciparum) Total 0 0 under 5 yrs 0 0 True malaria cases 5 yrs & above 0 0 (non P. falciparum ) Total 0 0 under 5 yrs #DIV/0! #DIV/0! % of fever cases treated 5 yrs & above #DIV/0! #DIV/0! Total #DIV/0! #DIV/0! under 5 yrs #DIV/0! #DIV/0! % of fever cases being true malaria 5 yrs & above #DIV/0! #DIV/0! Total #DIV/0! #DIV/0! under 5 yrs #DIV/0! #DIV/0! Ratio treated ACT/true pf cases 5 yrs & above #DIV/0! #DIV/0! Total #DIV/0! #DIV/0! Public sector onl Age group 2008 2009 under 5 yrs 0 0 Fever cases 5 yrs & above 0 0 Total 0 0 under 5 yrs 0 0 Diagnostic tests 5 yrs & above 0 0 (micro or RDT) Total 0 0 under 5 yrs #DIV/0! #DIV/0! % fever cases diagnosed 5 yrs & above #DIV/0! #DIV/0! (micro or RDT) Total #DIV/0! #DIV/0! under 5 yrs #DIV/0! #DIV/0! Cases treated with ACT 5 yrs & above #DIV/0! #DIV/0! Total #DIV/0! #DIV/0! under 5 yrs #DIV/0! #DIV/0! True malaria cases True malaria cases 5 yrs & above #DIV/0! #DIV/0! Total #DIV/0! #DIV/0! under 5 yrs #DIV/0! #DIV/0! True malaria cases 5 yrs & above #DIV/0! #DIV/0! (P. falciparum) Total #DIV/0! #DIV/0! under 5 yrs #DIV/0! #DIV/0! True malaria cases 5 yrs & above #DIV/0! #DIV/0! (non P. falciparum ) Total #DIV/0! #DIV/0! under 5 yrs #DIV/0! #DIV/0! % of fever cases treated 5 yrs & above #DIV/0! #DIV/0! Total #DIV/0! #DIV/0! under 5 yrs #DIV/0! #DIV/0! Ratio treated ACT/true pf cases 5 yrs & above #DIV/0! #DIV/0! Total #DIV/0! #DIV/0! Total population 2010 2011 2012 2013 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! Public sector only 2010 2011 2012 2013 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! ` Total Population at Risk for Malaria 1 1 1 1 1 Fever cases Diagnostic tests ACT treatments 1 Malaria Cases pf cases 0 non-pf cases 0 0 0 0 2008 2009 2010 2011 2012 2013 Public Sector Only 1 1 1 1 1 Fever cases Diagnostic tests ACT treatments 1 Malaria Cases pf cases 0 non-pf cases 0 0 0 0 2008 2009 2010 2011 2012 2013 Population estimates country other pop07 0 Country 2007 2008 2009 growth rate** 2.5% Population* 0 0 0 pers/hh*** 5 Households 0 0 0 %U5 16.5% %PW 4.5% Children 0-4 0 0 0 %pop/yr 0-4 3.2% Persons 5+ 0 0 0 %pop/yr 5-9 2.8% Infants 0 0 0 %pop/yr 10-14 2.5% %>14 57.5% Pregnant Women 0 0 0 At risk for malaria Population 0 0 0 Households 0 0 0 Children 0-4 0 0 0 Persons 5+ 0 0 0 Infants 0 0 0 Pregnant Women 0 0 0 * from US Census Bureau estimates unless entered manually ** from 2007 Population Data Sheet, Population Reference Bureau unless entered manuall *** from Globalhealth.org website unless entered manually 2010 2011 2012 2013 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Bureau unless entered manually 1. Treatment Mean Episodes/Person/Year by endemicity level at baseline* Fever Malaria Age High Low High Low <5 4.5 3.0 2.5 1.0 5+ 1.8 1.4 0.8 0.4 * they are then reduced to a max of 85% by interventions Figure1 : Detailed fever incidence rates 7.00 Fever episodes/person/year 6.00 5.00 4.00 high 3.00 low 2.00 1.00 0.00 + 10 11 13 14 0 1 2 3 4 5 6 7 8 9 12 15 Age in years 2. ITN Mean number of ITN per household as a function of household size and ITN coverage ITN Household size (persons) coverage <4.5 4.5-5.5 >5.5 4.5% 1.3 1.5 1.7 13.8% 1.4 1.6 1.8 22.0% 1.5 1.7 1.9 32.0% 1.6 1.8 2 40.5% 1.7 1.9 2.1 49.0% 1.8 2 2.2 57.0% 1.9 2.1 2.3 66.0% 2 2.2 2.4 75.0% 2.1 2.3 2.5 83.0% 2.2 2.4 2.6 91.0% 2.3 2.5 2.7 100.0% 2.4 2.6 2.8 100% Figure 2: Loss function by net type over time (years) 100% 90% Polyethylene 80% Polyester 70% 60% 50% 40% 30% 20% 10% 0% 0 2 4 6 8 10 12 14 16 18