A: Total population B: Total # of WRA in the country/region/district - PowerPoint Presentation

1. A: Total populationB: Total # of WRA in the country/region/district = A × % of WRAC: # of WRA who use short-acting modern methodsC1 = B × CPR in % of male condoms;C2 = B × CPR in % of female condoms;C3 = B × CPR in % of oral pills;C4 = B × CPR in % of injectablesH: # of WRA with a need for ECP = D + E + GK: # of WRA who have access to ECP from the public sector= J × % with access from public sectorI: # of WRA who are aware of ECP = H × % who are aware of ECPsE: # of WRA with unmet contraception need= B × % of unmet modern contraception methods)D: # of WRA having contraception failure D = D1 + D2 + D3 + D4; where D1 = C1 × failure rate in % of male condoms;D2 = C2 × failure rate in % of female condoms;D3 = C3 × failure rate in % of oral pills;D4 = C4 × failure rate in % of injectablesG: WRA at risk of pregnancy due to rape per year = B × incidence of rape in % × (100% - F)J: # of WRA who have access to/use ECP = I × % who have access to and use ECPsL: # of WRA who have access to ECP from the SM sector= J × % with access from SM sectorM1: # who use levonorgestrel 1.5 mg = K × % who use levonorgestrel 1.5 mgM2: # who use levonorgestrel 0.75 mg = K × % who use levonorgestrel 0.75 mgN1: # who use levonorgestrel 1.5 mg= L × % who use levonorgestrel 1.5 mgN2:. # who use levonorgestrel 0.75 mg = L × % who use levonorgestrel 0.75 mgP1 & P2. Quantity of levonorgestrel 1.5 mg tab (blister of 1 tab) by sectorP1: Qty. for public sector = M1 x O; P2: Qty. for SM sector = N1 × O; where O = 1 blister of 1 tabR1 & R2. Quantity of levonorgestrel 0.75 mg tab (blister of 2 tabs) by sectorR1: Qty. for public sector = M2 × Q; R2: Qty. for SM sector = N2 × Q; where Q = 1 blister of 2 tabs S. Total quantity of levonorgestrel 1.5 mg tab (blister of 1 tab) = P1 + P2T. Total quantity of levonorgestrel 0.75 mg tab (blister of 2) = R1 + R2F: Total CPR in % for modern methodsForecasting algorithm for ECP based on morbidity/demographic method

2. A: Total populationB: Total # of WRA in the country/region/district = A × % of WRAD: # of public sector contraceptive implant users= C × % users from public sectorC: Total # of WRA who use contraceptive implants = B × CPR in % for contraceptive implantsE: # of SM sector contraceptive implant users = C × % users from SM sector F: # of public sector implant users by type/brandF1: Levonorgestrel 75 mg/rod:2-rod-5 year = D × % who use 2-rod 5-year typeF2: Levonorgestrel 75 mg/rod:2-rod 3-year = D × % who use 2-rod 3-year typeF3: Levonorgestrel 68 mg/rod:1-rod 3-year = D × % who use 1-rod 3-year typeG: # of SM sector implant users by type/brandG1: Levonorgestrel 75 mg/rod:2-rod 5-year = E × % who use 2-rod 5-year typeG2: Levonorgestrel 75 mg/rod:2-rod 3-year = E × % who use 2-rod 3-year typeG3: Levonorgestrel 68 mg/rod:1-rod 3-year = E × % who use 1-rod 3-year typeK: Quantity of each brand/type needed in the public and SM sector K1: Levonorgestrel 75 mg/rod, 2-rod 5-year = H1 + J1K2: Levonorgestrel 75 mg/rod, 2-rod 3-year = H2 + J2 K3: Levonorgestrel 68 mg/rod, 1-rod 3-year = H3 + J3H: # of users who need insertion of implants in the public sector by type/brand in each year = (F – users in the previous year) + (number of users who discontinue use during the current year*)]; and# of users who discontinue use in current year = # of users in the previous year x discontinuation rate (%)Example: H1: # that need insertion of Levonorgestrel 75 mg/rod, 2-rod 5-year = (F1 – users in the previous year) + (# of users in the previous year x discontinuation rate in %)J: # of users who need insertion of implants in the SM sector by type/brand in each year = (G – users in the previous year) + (number of users who discontinue use during the current year*)]; and# of users who discontinue use in current year = # of users in the previous year x discontinuation rate (%)Example: J1: # that need insertion of Levonorgestrel 75 mg/rod, 2-rod 5-year = (G1 – users in the previous year) + (# of users in the previous year x discontinuation rate in %)Forecasting algorithm for contraceptive implants based on morbidity/demographic method

3. A: Total populationB: Total # of women 15-59 years in the country/region/district = A × % of 15-59 years of ageC: # of sexually active women 15-59 years, excluding CSWs = B × % sexually active women 15-59 yearsI: # of sexually active women 15-59 years, excluding CSWs, who are aware of and use female condoms= G × % who are aware of and use female condomsE: # of sexually active women 15-59 years, excluding CSWs with a need for female condoms= C × % sexually active women 15-59 years with a need for female condomsK: # of sexually active women 15-59 years, excluding CSWs, who have access to female condoms by sector K1: Public sector = I × % with access from public sectorK2: SM sector = I × % with access from SM sectorD: # of CSWs = B × % CSWsF: # of CSWs with a need for female condoms= D × % CSWs with a need for female condomsG: # of sexually active women 15-59 years, excluding CSWs, who are aware of female condoms= E × % who are aware of female condomsH. # of CSWs who are aware of female condoms= F × % who are aware of female condomsJ: # of CSWs who are aware of and use female condoms = H × % who are aware of and use female condomsL: # of CSWs who have access to female condoms by sectorL1: Public sector = J × % with access from public sectorL2: SM sector = J × % with access from SM sectorN: # of female condoms required by sexually active women 15-59 years, excluding CSWs, by sectorN1: public sector = K1 × M; N2: SM sector = K2 × M;where M = CYP = # of female condoms per women per year = 120 P: # of female condoms required by CSWs by sectorP1: public sector = L1 × O; P2: SM sector = L2 × O;where O = CYP = # of female condoms per CSW per year = 120 R: Total # of female condoms required per year (public and SM sectors)= Q1 + Q2 Q: Quantity of female condoms required for each sectorQ1: Qty needed for Public sector = N1 + P1 Q2: Qty needed for Social marketing sector = N2 + P2 Forecasting algorithm for female condoms based on morbidity/demographic method

4. A: Total populationB: Total pregnancies = A× % of pregnanciesC: Total deliveries = B × [100% - miscarriage rate (%)]D: # of public HF deliveries = C × % of deliveries in public HFsG: # of home deliveries = C × % of deliveries at homeE: # of public HF deliveries provided with prevention for PPH= D × % provided with prevention for PPHH: # of home deliveries provided with prevention (misoprostol) for PPH= G × % provided with misoprostol for PPH preventionF: # of public HF deliveries provided with a specific uterotonic for prevention of PPH = E × % to be given specific uterotonic for PPH preventionF1: # provided oxytocin = E x % given oxytocinF2: # provided misoprostol = E x % given misoprostolF3: # provided HSC = E x % given HSCL: Total qty. of each medicine needed for prevention of PPH (public HF + home)= Qty. of each uterotonic required for public HF deliveries + qty. of each uterotonic required for home deliveriesL1: quantity of oxytocin needed = J1L2: quantity of misoprostol needed = J2 + KL3: quantity of HSC needed = J3J: Qty. of each uterotonic required for the public HFs = F × I; J1 = F1 × I1; J2 = F2 × I2; J3 = H × I2;where I = average quantity of each uterotonic per caseI1: Oxytocin 10 IU amp = 1 amp; I2: misoprostol 200 mcg tab = 3 tabs; I3: HSC 100 mcg amp = 1 ampK: Qty. of each uterotonic required for home deliveries = H × I; K = H × I2where I = average quantity of each uterotonic per caseI2: misoprostol 200 mcg tab = 3 tabs; Forecasting algorithm for medicines used for prevention of PPH based on morbidity method

5. X: Qty. of each medicine required to treat PPH cases = # of PPH cases treated with each medicine by group × V; X1 = V1 × W1; X2 = V2 × W2;X3 = V3 × W3;Where, W = average quantity of each medicine per case W1= 4 amps of oxytocin 10 IU ampW2 = 4 tablets of misoprostol 200 mgW3 = 1 amp of TXA 1 gA: Total populationB: Total pregnancies = A × % of pregnanciesC: Total deliveries = B × [100% - miscarriage rate (%)]E: # of public HF deliveries provided with prevention for PPH= D × % provided with prevention for PPHH: # of home deliveries provided with prevention for PPH= G × % provided with prevention for PPHV: # of PPH cases treated with a specific medicine/regimen= (P + U) × % to be given specific medicine for PPH treatmentV1 = (P + U) × % treated with oxytocinV2 = (P + U) × % treated with misoprostolV3 = (P + U) × % treated with TXAM: # of public HF deliveries NOT provided with prevention for PPH= D × % NOT provided with prevention for PPHQ: # of home deliveries NOT provided with prevention for PPH= G × % NOT provided with prevention for PPHN: # of public HF deliveries that develop PPH after prevention= E × incidence of PPH after preventionP: # of public HF PPH cases treated= (N + O) × % treated at public HFs R: # of home deliveries that develop PPH after prevention= H × incidence of PPH after preventionT: # of home PPH cases referred to public HFs= (R + S) × % referred to public HFs for treatment O: # of public HF deliveries that develop PPH without prevention= M × incidence of PPH without prevention S: # of home deliveries that develop PPH without prevention= Q × incidence of PPH without preventionD: # of public HF deliveries = C × % of deliveries in public HFsG: # of home deliveries = C × % of deliveries at homeU: # of home PPH cases treated = T × % treated at public HFs Forecasting algorithm for medicines used for treatment of PPH based on morbidity method

6. H: # of severe hypertensive cases treated: public hospitals= F x % treated with antihypertensivesA: Total populationB: Total pregnancies = A x % of pregnanciesC: # of pregnancies with severe hypertension = B x Incidence of severe hypertension D: # of pregnancies with severe hypertension identified at public HFs = C x % of cases identified at public health facilitiesO. Quantity of each medicine required to treat severe hypertension in pregnancies in the public sectorO1: Quantity of methyldopa 250mg tab = L1 + N1;O2: Quantity of labetalol 200mg tab = L2 + N2a;O3: Quantity of labetalol 20mg/2ml sol. for inj. in amp = N2b;O4: Quantity of hydralazine 20mg powder for inj. in 2ml vial = N3; Plus other medicines*E: # of pregnancies with severe hypertension at 1st level public HFs= D x % identified at 1st level public HFsF: # of pregnancies with severe hypertension: public hospitals= D x % identified at public hospitalsG: # of severe hypertensive cases treated at 1st level public HFs= E x % treated with antihypertensivesI: # of 1st level public HF severe hypertensive cases treated with specific regimensI1: # treated with methyldopa = G x % treated with methyldopaI2: # treated with labetalol = G x % treated with the labetalolPlus other regimensL: Quantity of each medicine required at 1st level public HFL1: Quantity of methyldopa 250mg tab = I1 x % treated x K; where K1: quantity per case =36 tabsL2: Quantity of labetalol 200mg tab = I2 x % treated x K2; where K2: quantity per case = 18 tabsPlus other medicines*N: Quantity of each medicine required in public hospitalsN1: Quantity of methyldopa 250mg tab = J1 x % treated x M1; where M1: quantity per case = 36 tabsN2a: Quantity of labetalol 200mg tab = J2 x % treated x M; where M2a: quantity per case =18 tabsN2b: Quantity of labetalol 20mg/2ml sol. for inj. in amp = J2 x % treated x M2b; where M2b = quantity per case = 45 ampsN3: Quantity of hydralazine 20mg powder for inj. in 2ml vials = J3 x % treated x M3; where M3: quantity per case = 3 vials Plus other regimens*J: # of public hospital severe hypertensive cases treated with specific regimensJ1: # treated with methyldopa = H x % treated with methyldopaJ2: # treated with labetalol = H x % treated with labetalolJ3: # treated with hydralazine = H x % treated with hydralazinePlus other regimensForecasting algorithm for medicines used for acute treatment of severe hypertension in pregnancy based on morbidity method

7. *All cases are assumed to be given MgSO4 only either for the prevention and treatment of eclampsia, according to WHO’s recommendation; and other anticonvulsants such as diazepam are not used. Refer to table x for more option on regimens types and quantity per caseB: Total pregnancies = Total population × % of pregnanciesD: # of pre-eclampsia cases at public HFs = C × incidence of pre-eclampsia E: # of public HF pregnancies with severe pre-eclampsia= D x incidence of severe pre-eclampsia F: # of severe pre-eclampsia cases given MgSO4 for prophylaxis of eclampsia = E × % given MgSO4 for prophylaxis of eclampsia C: # of pregnancies at public HFs = B × % of pregnancies attending ANC in public HFsA: Total populationH: Quantity of MgSO4 required for prophylaxis of eclampsiaH = F × G;where G = 9 ampoules of MgSO4 5 g/10 ml*; OR 44 ampoules of MgSO4 1 g/2 ml*K: # of public HF eclampsia cases treated with MgSO4= (I+J) x % treatedR. Total quantity of MgSO4 required for prophylaxis and treatment of eclampsia= H + QM: No. of home pregnancies with eclampsia= L x Incidence of eclampsia N: # of home pregnancies with eclampsia that are referred to public HFs= M x % referred to public HFs I: # of public HF severe pre-eclampsia cases that develop eclampsia after prophylaxis= F x Incidence of eclampsia after prophylaxisJ: # of public HF severe pre-eclampsia cases not given MgSO4 for prophylaxis that develop eclampsia = (E-F)x Incidence of eclampsia without prophylaxisO: # of eclampsia cases treated at public HFs= N x % treated Q: Quantity of MgSO4 required for treatment of eclampsia= (K+O) x P; where P : quantity per case = 9 ampoules of MgSO4 5g/10ml*; OR 44 ampoules of MgSO4 1g/2ml*L: No. of home pregnancies= B x % of home pregnanciesForecasting algorithm for MgSO4 used for prophylaxis and treatment of eclampsia based on morbidity method

8. A: # of public HFs by type where MgSO4 is supposed to be used for prevention and treatment of eclampsiaA1: Referral hospitals; A2: Regional hospitals; A3: District hospitals;A4: Health centers;Plus other health facilities*D: Total quantity of MgSO4 5 g/10 ml; or MgSO4 1 g/2 ml ampoules needed per year= C1 + C2 + C3 + C4 + …C: Quantity of MgSO4 5 g/10 ml; or MgSO4 1 g/2 ml ampoules needed per year per facility typeC1: quantity for referral hospitals = A1 x B1; where B1 = average quantity per referral hospital per yearC2: quantity for regional hospitals = A2 x B2; where B2 = average quantity per regional hospital per year C3: quantity district hospitals = A3 x B3; where B3 = average quantity per district hospital per yearC4: quantity for health centers = A4 x B4; where B4 = average quantity per health center per yearPlus quantity for other health facilities*Notes:Average quantity of allocation per facility level per year shall consider: the incidence of the cases by level, capacity to administer the products ( for example health center may be allowed to administer the loading/pre-referral dose only) and the minimum possible pack size for distribution to health facilities.* consider other health facility types, or sub-groups of the ones indicated above, and medicines as applicable to the local contextOnce MgSO4 and calcium gluconate are distributed based on the allocation, the morbidity method can be used to estimate actual demand and replenish what is used during each year of the quantification period; expiry dates should be considered, though. Alternatively, the quantification team may use a combination of the two methods of forecasting, applying the allocation methods for the health facilities where the number of cases is estimated to be low (such as health centers) and applying the morbidity method for those health facility types that have relatively high incidence of cases that allows smooth distribution of the medicines considering the lowest distribution pack sizes. Forecasting algorithm for MgSO4 used for prophylaxis and treatment of eclampsia based on allocations by facility type

9. A: # of public HFs by type where MgSO4 is supposed to be used for prevention and treatment of eclampsiaA1: Referral hospitals; A2: Regional hospitals; A3: District hospitals;A4: Health centers;Plus other health facilities*D: Total quantity of calcium gluconate 1g/10ml, 10 ml ampoules needed per year= C1 + C2 + C3 + C4 + …Plus quantities for other level *C: Quantity of calcium gluconate 1g/10ml, ampoules needed per year per facility typeC1: quantity for referral hospitals = A1 x B1; where B1 = average quantity per referral hospital per yearC2: quantity for regional hospitals = A2 x B2; where B2 = average quantity per regional hospital per year C3: quantity for district hospitals = A3 x B3; where B3 = average quantity per district hospital per yearC4: quantity for health centers = A4 x B4; where B4 = average quantity per health center per yearPlus quantity for other health facilities*Notes:Average quantity of allocation per facility level per year shall consider: the incidence of the cases by level, capacity to administer the products and the minimum possible pack size for distribution to health facilities.* Please consider other health facility types, or sub-groups of the ones indicated above, as applicable to the local contextForecasting algorithm for calcium gluconate used to treat toxicity of MgSO4 based on allocations by facility type

10. A: Total populationB: Total pregnancies = A × % of pregnanciesC: # of pregnancies attending ANC at public HFs= B × % attending ANC at public HFsD: Public HF pregnancies at risk of preterm birth= C × incidence of preterm birthH: Quantity of each ACS required H1: Qty. of dexamethasone 4 mg/ml amp = F1 × G1; where G1: average qty. of dexamethasone 4 mg/ml amp per case = 6 or 8 ampsORH2: Qty. of betamethasone 6 mg/ml vial =F2 x G2; where G2: average qty. of betamethasone 6 mg/ml vial per case = 4 vialsE: # of pregnancies at risk of preterm birth likely to be given ACSs = D × % given ACSsF: # of public HF preterm birth pregnancies given specific ACSsF1: # treated with dexamethasone = E × % treated with dexamethasone ORF2: # treated with betamethasone = E × % treated with betamethasoneForecasting algorithm for ACS based on morbidity method

11. B: Average # of rooms where reusable resuscitation devices are required by type of public HFD: Total # of rooms where reusable resuscitation devices are required by type of public HF = A × BE: Total # of reusable resuscitation devices required for each type of the public HF = C × DF: Total # of reusable resuscitation devices required for all types of public HFs= Sum the qty. of reusable resuscitation devices required by each type of health facility in the country/region i.e. Sum of EsC: Average # of reusable resuscitation devices per room for each type of public HFA: Total # of public HFs by typeForecasting algorithms for reusable resuscitation devices (bag and mask and multiuse suction device) based on allocation by facilities

12. A: Total populationE: # of public HF birth that need suction and resuscitation devices= D × % of live births that need suction and resuscitation devicesD: # of public HF live births= C× % of public HF live birthsH: Quantity of single-use suction bulbs required at public HFs= F × G ; where G: quantity per case = 1C: Total live births = A × B; where B = CBRF: # of public HF live births that need single-use suction bulbs = E × % of cases estimated to use single-use suction bulbsForecasting algorithm for single use suction bulb (device) based on morbidity method

13. H: Proportion of cases given specific regimens of chlorhexidine at public HFs (single-day or seven-day regimen)= F × % given single-day regimen; OR = F × % given seven-day regimenA: Total populationC: Total live births = A × B; where B = CBR F: # of infants that receive chlorhexidine for umbilical care at public HFs= D × % given chlorhexidineD: # of public HF live births= C× % of public HF live birthsE: # of home live births= C × % of home live birthsG: # of infants that receive chlorhexidine for umbilical care at home= E × % given chlorhexidineM. Total qty. of each formulation of chlorhexidine used per year= Qty. used at public HF + qty. used at homeM1: Qty. of chlorhexidine 7.1% gel 20 g, tube = K1 + L1; ORM2: Qty. of chlorhexidine 7.1% gel 3 g, sachet = K2 + L2I: Proportion of cases given specific regimens of chlorhexidine at home (single-day or seven-day regimen)= G × % given single-day regimen; OR = G × % given seven-day regimenK: Qty. of each formulation of chlorhexidine needed at public HFs K1: Chlorhexidine 7.1% gel 20 g tube = H × J1OR K2: Chlorhexidine 7.1% gel 3 g, sachet = H × J2where J: quantity per one case J1 = 1 tube of chlorhexidine 7.1% gel 20 g; J2 = 1 or 7 sachets of chlorhexidine 7.1% gel 3 g , for 1-day or 7-day regimen, respectivelyL: Qty. of each formulation of chlorhexidine needed at home L1: Chlorhexidine 7.1% gel 20 g tube = I × J1OR L2: Chlorhexidine 7.1% gel 3 g, sachet = I × J2where J: quantity per one case J1 = 1 tube of chlorhexidine 7.1% gel 20 g; J2 = 1 or 7 sachets of chlorhexidine 7.1% gel 3 g , for 1-day or 7-day regimen, respectivelyForecasting algorithm for chlorhexidine digluconate used for infant cord care based on morbidity method

14. A: Total populationC: Total live births = (A/1000) × B; where B = CBR*D: Total number of PSBI or Very Severe Disease cases in infants 0-59 days = C× incidence of PSBI or Very Severe Disease in infants 0-59 daysE: Number of PSBI or Very Severe Disease 0-59 day cases treated in the public sector = D × % of cases treated in the public sectorF1: Treated at 1st level HFs= F × % treated at 1st level HFsF2: Treated at hospitals= F × % treated at hospitalsF: # of severe pneumonia (fast breathing) 0-6 day cases treated= E × % of cases treatedG: # of severe pneumonia (fast breathing) 7-59 day cases treated = E × % of cases treatedH: # of 0-59 day clinical severe infection cases treated= E × % of 0-59 day clinical severe infection cases treatedI: # of 0-59 day with critical illness cases treated= E × % of 0-59 day critical illness cases treatedG1: Treated at 1st level HFs= G × % treated at 1st level HFsG2: Treated at hospitals= G × % treated at hospitalsH1: Treated at 1st level HFs= H × % treated at 1st level HFsH2: Treated at hospitals = H × % treated at hospitalsI1: Treated at 1st level HFs= I × % treated at 1st level HFsI2: Treated at hospitals= I × % treated at hospitalsJ: # of severe pneumonia (fast breathing) 0-6 day cases treated with specific regimens by level of care K: # of severe pneumonia (fast breathing) 7-59 day cases treated with specific regimens by level of careL: # of 0-59 day cases with clinical severe infection treated with specific regimens by level of care:M: # of 0-59 day cases with critical illness treated with specific regimens by level of care:J1: # treated with 7-day oral amoxicillin at 1st level HFs = F1J2: # treated with 10-day gentamicin (IV/IM) and 10 day ampicillin (IV/IM) at hospitals = F2J3: # treated with 10-day ceftriaxone (IV/IM) at hospitals = F2 x % that need 2nd line treatmentPlus other regimens****K1: # treated with 7-day oral amoxicillin at 1st level HFs= G1K2: # treated with 7-day oral amoxicillin at hospitals = G2K3: # treated with 10-day ceftriaxone (IV/IM) at hospitals = G2 x % that need 2nd line treatmentL1: # treated with 2-day or 7-day gentamicin (IM)* and 7-day oral amoxicillin at 1st level HFs = H1L2: 10-day gentamicin (IV/IM) and 10-day ampicillin (IV/IM) at hospitals = H2L3: 10-day ceftriaxone (IV/IM) at hospitals = H2 x % treated with 2nd line regimenPlus other regimens****M1: # treated with 7-day gentamicin (IM) and 7-day ampicillin (IM) at 1st level HFs = I1M2: # treated with 10-day gentamicin (IV/IM) and 10-day ampicillin (IV/IM) at hospitals = I2M3: # treated with 10-day ceftriaxone (IV/IM) at hospitals = I2 x % treated with 2nd line regimenPlus other regimens****N: Qty. of each medicine required to treat a PSBI or very severe disease case at 1st-level HFs = # of cases treated with each medicine by group × average quantity of each medicine per case (O)**N1: Amoxicillin 250 mg DT = [(J1 + K1 + L1)) × O1]; where O1 = 7 tabletsN2: Gentamicin 40 mg/ml, 2 ml vials = [(L1 x O2) + (M1 × O3)]; where O2 = 7 or 2*** vials and O3 = 7 vialsN3: Ampicillin 500 mg vials = [M1 × O4]; where O4 = 14 VialsPlus other medicines****P: Qty. of each medicine required to treat PSBI or very severe disease cases at hospitals = # of cases treated with each medicine by group × average quantity of each medicine per case (Q)**P1: Amoxicillin 250 mg DT = [K2 × Q1]; where Q1 = 7 tabletsP2: Gentamicin 40 mg/ml, 2 ml vials = [(J2 + L2 + M2)) × Q2]; where Q2 = 10 vialsP3: Ampicillin 500 mg vials = [(J2 + L2 + M2)) × Q3]; where Q3 = 30 vialsP4: Ceftriaxone 250 mg vials = [(J3 + K3 + L3 + M3) × Q4]; where Q4 = 10 vialsPlus other medicines ****R: Qty. of each medicine required to treat all PSBI or very severe disease cases in the public sector[= Qty. required for 1st-level HFs + Qty. required in hospitals, by medicine]; i.e. R = N + PPlus other medicines****R1: Amoxicillin 250 mg DT = N1 + P1R2: Gentamicin 40 mg/ml, 2 ml vials = N2 + P2; R3: Ampicillin 500 mg vials = N3 + P3R4: Ceftriaxone 250 mg vials = P4;Forecasting algorithm for antibiotics used to treat PSBI or very severe disease in newborns based on morbidity method

15. H: # of 2-59 m pneumonia cases treated by type: public hospitalH1: # of fast-breathing cases = E3 × % of fast-breathing pneumonia treated; H2: # of HIV- ve and chest-in-drawing cases = E3 × % of HIV-ve and chest-in-drawing pneumonia treatedH3: # of severe, or HIV + ve chest-in-drawing cases = E3 × % of severe, or HIV+ ve chest-in-drawing pneumonia F: # of 2-59 m pneumonia cases treated by type: Community levelF1: # of fast-breathing cases = E1 × % of fast-breathing pneumonia treated* * Assumes only fast breathing cases are treated at community levelA: Total populationB: Total population of 2-59m = A × % of 2-59 m C: # of under 2-59 m pneumonia cases = B × incidence of pneumoniaD: # of under 2-59 m pneumonia cases treated in public health care services, including CHWs = C × % of cases treated in public sector servicesE: # of 2-59 m pneumonia cases treated by level of care E1: # at community level (by CHWs) = D × % treated at community level;E2:. # at 1st-level public HFs = D × % treated at 1st-level public HFs;E3: # at public hospitals = D × % treated at public hospitalsG: # of 2-59 m pneumonia cases treated by type: 1st-level public HFsG1: # of fast-breathing cases = E2 × % of fast-breathing pneumonia treatedG2: # of HIV-ve and chest-in-drawing cases = E2 × % of HIV- ve and chest-in-drawing pneumonia treatedJ: # of 2-59 m pneumonia cases treated with specific regimen: 1st-level public HFsJ: # treated with 5-day oral amoxicillin = (G1 + G2) × % treated with the regimen I: # of 2-59 m pneumonia cases treated with specific regimen: Community levelI: # treated with 5-day oral amoxicillin = F × % treated with the regimenR: Qty. of each medicine required to treat 2-59 m pneumonia cases in public sector= Qty. for Community (M) + Qty. for 1st-level public HFs (O) + Qty. for public hospitals (Q)R1: Amoxicillin 250 mg DT = (M1 + M2) + (O1 + O2 + O3) + (Q1 + Q2 + Q3)Plus other medicinesM: Qty. of each medicine required by age group: Community levelM1: Amoxicillin 250 mg DT for 2-11 m = I × % of age group × L1; where L1: Qty per case = 10 DTsM2: Amoxicillin 250 mg DT for 12-59m = I × % of age group × L2; where L2: Qty per case = 20 DTsK: # of 2-59 m pneumonia cases treated with specific regimen: public hospitalsK1: # treated with 5-day oral amoxicillin = (H1 + H2) × % treated with the regimen;K2: # treated with 5-day gentamicin IV/IM and ampicillin IV/IM = H3 × % treated with the regimenPlus other regimensO: Qty. of each medicine required by age group: 1st-level public HFsO1: Amoxicillin 250 mg DT for 2-11 m = J × % of age group × N1; where N1: Qty per case =10 DTs O2: Amoxicillin 250 mg DT for 12-36 m = J × % of age group × N2; where N2: Qty per case =20 DTs O3: Amoxicillin 250 mg DT for 37-59 m = J × % of age group × N3; where N3: Qty per case =30 DTsQ: Qty. of each medicine required by age group: Public hospitalsQ1: Amoxicillin 250 mg DT for 2-11m = K1 × % of age group × P1; where P1: Qty per case =10 DTs Q2: Amoxicillin 250 mg DT for 12-36 m = K1 × % of age group × P2; where P2= Qty per case =20 DTsQ3: Amoxicillin 250 mg DT for 37-59 m = K1 × % of age group × P3; where P3: Qty per case =30 DTsPlus other medicinesForecasting algorithm for antibiotics used to treat pneumonia in children 2–59 months based on morbidity method

16. K: Qty. of each medicine required by age group: Community levelK1: Amoxicillin 250 mg DT for 2-11 m = H × % of age group × J1; where J1: Qty per case = 10 DTsK2: Amoxicillin 250 mg DT for 12-59m = H × % of age group × J2; where J2: Qty per case = 20 DTsG: # of 2-59 m pneumonia cases treated by type: Public HFs**G1 = E2 × % of fast breathing cases treated at public HFsG2 = E2 × % of HIV-ve and Chest-indrawing cases treated at public HFsF: # of 2-59 m pneumonia cases treated by type : Community level*F = E1 × % of fast breathing cases treated at community levelA: Total populationB: Total population of 2-59m = A × % of 2-59 m C: # of under 2-59 m pneumonia cases = B × incidence of pneumoniaD: # of under 2-59 m pneumonia cases treated in public health care services, including CHWs = C × % of cases treated in public sectorH: # of 2-59 m pneumonia cases treated with specific regimen: Community level*H: # treated with 5-day oral amoxicillin = F × % treated with the regimenN: Qty. of each medicine required to treat 2-59 m pneumonia cases in public sector= Qty. for Community (K) + Qty. for public HFs (M) N1 Qty of Amoxicillin 250 mg DT = (K1 + K2) + (M1 + M2 + M3)I. # of 2-59 m pneumonia cases treated with specific regimen: Public HFs*H: # treated with 5-day oral amoxicillin = (G1+G2) × % treated with the regimen;M: Qty. of each medicine required by age group: Public HFsM1: Amoxicillin 250 mg DT for 2-11m = I × % of age group × L1; where L1: Qty per case =10 DTs M2: Amoxicillin 250 mg DT for 12-36 m = I × % of age group × L2; where L2= Qty per case =20 DTsM3: Amoxicillin 250 mg DT for 37-59 m = I × % of age group × L3; where L3: Qty per case =30 DTsE: # of 2-59 m pneumonia cases treated by level of care E1: # at community level (by CHWs) = D × % treated at community level;E2:. # at 1st-level public HFs = D × % treated at public HFs;Forecasting algorithm for amoxicillin used to treat nonsevere pneumonia in children 2–59 months based on morbidity method (simplified version)

17. Forecasting algorithm for products used to treat diarrhea in children under 5 based on morbidity methodA: Total populationB: Total population of under 5 years = A × % of <5 years C: # of under 5-year diarrhea cases = B × incidence of diarrheaD: # of under 5-year diarrhea cases treated in public health care services, including CHWs = C × % of cases treated in public sector servicesE: # of under 5-year diarrhea cases treated by level of care E1: # at community level (by CHWs) = D × % treated at community level;E2: # at 1st-level public HFs = D × % treated at 1st-level public HFs;E3: # at public hospitals = D × % treated at public hospitalsF: # of under 5-year diarrhea cases treated by type at community level by CHWs*F: # of non-severe diarrhea without blood = E1 x % of non-severe diarrhea without blood treatedG: # of under 5-year diarrhea cases treated by type at 1st level public HFs*G: # of non-severe diarrhea = E2 x % of non-severe diarrhea treated H: # of under 5-year diarrhea cases treated by type at public hospitals*H1: # of non-severe diarrhea = E3 x % of non-severe diarrhea treated; H2: # of severe diarrhea = E3 x % of severe diarrhea treatedJ: # of under 5-year diarrhea cases treated with specific regimen at 1st level public HFsJ1: # non-severe without blood treated with 2-day ORS & 10-day Zinc= G x % treated with the regimen;J2: # non-severe with blood treated with 2-day ORS, 10-day Zinc & 3-day Ciprofloxacin or 5-day Metronidazole = G x % treated with the regimenI: # of under 5-year diarrhea cases treated with specific regimen at community level by CHWsI: # non-severe without blood treated with 2-day ORS & 10-day Zinc = F x % treated with the regimenS: Quantity of each medicine required to treat under 5-year diarrhea cases in public sector= Community (N) + 1st level public HFs (P) + Public hospitals (R)S1: ORS low Osm. 20.5g sachets = N1 + P1 + R1S2: Zinc 20mg DT = N2a + N2b + P2a + P2b + R2a + R2bPlus other medicinesN: Quantity of each medicine required by age group: Community level (CHWs)N1: ORS 20.5g = I x M1; where M1: quantity per case = 2 sachets;N2a: Zinc 20mg DT for 2-5m = I x % treated x M2a; where M2a: quantity per case = 5 DTs N2b: Zinc 20mg DT for 6-59m = I x % treated x M2b; where M2b: quantity per case = 10 DTsK and L: # of under 5-year diarrhea cases treated with specific regimen: public hospitalsK1: # non severe diarrhea without blood treated with 2-day ORS & 10-day Zinc = H1 x % treated with the regimenK2: # non severe diarrhea with blood treated with 2-day ORS, 10-day Zinc & 3-day Ciprofloxacin or 5-day Metronidazole = H1 x % treated with the regimen;L1: # severe diarrhea without blood treated with Ringer's solution stat, 2-day ORS and 10-day Zinc = H2 x % treated with the regimen;L2: # severe diarrhea with blood treated with Ringer's solution stat, 2-day ORS, 10-day Zinc, 3-day Ceftriaxone or 5-day Metronidazole = H2 x % treated with the regimenP: Quantity of each medicine required by age group at 1st level public HFsP1: ORS 20.5g = (J1+J2) x O1; where O1: quantity per case = 2 sachets P2a: Zinc 20mg DT for 2-5m = (J1+J2) x % treated x O2a; where O2a: quantity per case = 5 DTs P2b: Zinc 20mg DT for 6-59m = (J1+J2) x % treated x O2b; where O2b: quantity per case = 10 DTsPlus other medicinesR: Quantity of each medicine required by age group at public hospitalsR1: ORS 20.5g = (K1+K2+L1+L2) x Q1; where Q1: quantity per case = 2 sachets R2a: Zinc 20mg DT for 2-5m = (K1+K2+L1+L2) x % treated x Q2a; where Q2a: quantity per case = 5 DTs R2b: Zinc 20mg DT for 6-59m = (K1+K2+L1+L2) x % treated x Q2b; where Q2b: quantity per case = 10 DTsPlus other medicines

18. A: Total populationB: Total population of under 5 years = A × % of <5 years C: # of under 5-year diarrhea cases = B × incidence of diarrheaD: # of under 5-year diarrhea cases treated in public health care services, including CHWs = C × % of cases treated in public sector servicesH: Quantity of each medicine required to treat under 5-year diarrhea cases in public sectorH1: ORS low Osm. 20.5g sachets = G1H2: Zinc 20mg DT = G2a + G2bE : # of under 5-year diarrhea cases treated with 2-day ORS and 10-day zinc= D x % treated with the regimenG: Quantity of each medicine required by age group G1: ORS 20.5g = E x F1; where F1: quantity per case = 2 sachets G2a: Zinc 20mg DT for 2-5m = E x % treated x F2a; where F2a: quantity per case = 5 DTs G2b: Zinc 20mg DT for 6-59m = E x % treated x F2b; where F2b: quantity per case = 10 DTsThis algorithm only takes into account ORS and zinc and no other antibiotics or fluids that may be needed for the more severe cases covered in the previous algorithmForecasting algorithm for ORS and zinc used to treat diarrhea in children under 5 based on morbidity method (simplified version)