Skip to main content
Top
Published in: Malaria Journal 1/2020

01-12-2020 | Malaria | Research

Sub-national stratification of malaria risk in mainland Tanzania: a simplified assembly of survey and routine data

Authors: Sumaiyya G. Thawer, Frank Chacky, Manuela Runge, Erik Reaves, Renata Mandike, Samwel Lazaro, Sigsbert Mkude, Susan F. Rumisha, Claud Kumalija, Christian Lengeler, Ally Mohamed, Emilie Pothin, Robert W. Snow, Fabrizio Molteni

Published in: Malaria Journal | Issue 1/2020

Login to get access

Abstract

Background

Recent malaria control efforts in mainland Tanzania have led to progressive changes in the prevalence of malaria infection in children, from 18.1% (2008) to 7.3% (2017). As the landscape of malaria transmission changes, a sub-national stratification becomes crucial for optimized cost-effective implementation of interventions. This paper describes the processes, data and outputs of the approach used to produce a simplified, pragmatic malaria risk stratification of 184 councils in mainland Tanzania.

Methods

Assemblies of annual parasite incidence and fever test positivity rate for the period 2016–2017 as well as confirmed malaria incidence and malaria positivity in pregnant women for the period 2015–2017 were obtained from routine district health information software. In addition, parasite prevalence in school children (PfPR5to16) were obtained from the two latest biennial council representative school malaria parasitaemia surveys, 2014–2015 and 2017. The PfPR5to16 served as a guide to set appropriate cut-offs for the other indicators. For each indicator, the maximum value from the past 3 years was used to allocate councils to one of four risk groups: very low (< 1%PfPR5to16), low (1− < 5%PfPR5to16), moderate (5− < 30%PfPR5to16) and high (≥ 30%PfPR5to16). Scores were assigned to each risk group per indicator per council and the total score was used to determine the overall risk strata of all councils.

Results

Out of 184 councils, 28 were in the very low stratum (12% of the population), 34 in the low stratum (28% of population), 49 in the moderate stratum (23% of population) and 73 in the high stratum (37% of population). Geographically, most of the councils in the low and very low strata were situated in the central corridor running from the north-east to south-west parts of the country, whilst the areas in the moderate to high strata were situated in the north-west and south-east regions.

Conclusion

A stratification approach based on multiple routine and survey malaria information was developed. This pragmatic approach can be rapidly reproduced without the use of sophisticated statistical methods, hence, lies within the scope of national malaria programmes across Africa.
Appendix
Available only for authorised users
Literature
2.
go back to reference Snow RW, Sartorius B, Kyalo D, Maina J, Amratia P, Mundia CW, et al. The prevalence of Plasmodium falciparum in sub Saharan Africa since 1900. Nature. 2017;550:515–8.CrossRef Snow RW, Sartorius B, Kyalo D, Maina J, Amratia P, Mundia CW, et al. The prevalence of Plasmodium falciparum in sub Saharan Africa since 1900. Nature. 2017;550:515–8.CrossRef
3.
go back to reference WHO, RBM Partnership to End Malaria. High burden to high impact: a targeted malaria response. Geneva, World Health Organization; 2019. Report No.: WHO/CDS/GMP/2018.25. WHO, RBM Partnership to End Malaria. High burden to high impact: a targeted malaria response. Geneva, World Health Organization; 2019. Report No.: WHO/CDS/GMP/2018.25.
4.
go back to reference WHO. Global technical strategy for malaria 2016–2030. Geneva: World Health Organization; 2015. WHO. Global technical strategy for malaria 2016–2030. Geneva: World Health Organization; 2015.
6.
go back to reference Bastiaens GJH, Bousema T, Leslie T. Scale-up of malaria rapid diagnostic tests and artemisinin-based combination therapy: challenges and perspectives in sub-Saharan Africa. PLoS Med. 2014;11:e1001590.CrossRef Bastiaens GJH, Bousema T, Leslie T. Scale-up of malaria rapid diagnostic tests and artemisinin-based combination therapy: challenges and perspectives in sub-Saharan Africa. PLoS Med. 2014;11:e1001590.CrossRef
7.
go back to reference National Malaria Control Programme (NMCP), Tanzania. National malaria strategic plan 2015–2020. Ministry of Health, Community Development, Gender, Elderly and Children; Tanzania; 2015. National Malaria Control Programme (NMCP), Tanzania. National malaria strategic plan 2015–2020. Ministry of Health, Community Development, Gender, Elderly and Children; Tanzania; 2015.
8.
go back to reference National Malaria Control Programme (NMCP), Tanzania. National malaria strategic plan 2008–2013. Ministry of Health, Community Development, Gender, Elderly and Children; Tanzania; 2008. National Malaria Control Programme (NMCP), Tanzania. National malaria strategic plan 2008–2013. Ministry of Health, Community Development, Gender, Elderly and Children; Tanzania; 2008.
9.
go back to reference National Malaria Control Programme (NMCP), Tanzania. National malaria strategic plan 2002–2007. Ministry of Health, Community Development, Gender, Elderly and Children; Tanzania; 2002. National Malaria Control Programme (NMCP), Tanzania. National malaria strategic plan 2002–2007. Ministry of Health, Community Development, Gender, Elderly and Children; Tanzania; 2002.
10.
go back to reference National Malaria Control Programme (Tanzania), WHO, Ifakara Health Institute, KEMRI-Wellcome Trust (Kenya). An epidemiological profile of malaria and its control in mainland Tanzania. Report funded by Roll Back Malaria and Department for International Development-UK; 2013. National Malaria Control Programme (Tanzania), WHO, Ifakara Health Institute, KEMRI-Wellcome Trust (Kenya). An epidemiological profile of malaria and its control in mainland Tanzania. Report funded by Roll Back Malaria and Department for International Development-UK; 2013.
11.
go back to reference Chacky F, Runge M, Rumisha SF, Machafuko P, Chaki P, Massaga JJ, et al. Nationwide school malaria parasitaemia survey in public primary schools, the United Republic of Tanzania. Malar J. 2018;17:452.CrossRef Chacky F, Runge M, Rumisha SF, Machafuko P, Chaki P, Massaga JJ, et al. Nationwide school malaria parasitaemia survey in public primary schools, the United Republic of Tanzania. Malar J. 2018;17:452.CrossRef
12.
go back to reference Runge M, Snow RW, Molteni F, Thawer S, Mohamed A, Mandike R, et al. Simulating the council-specific impact of anti-malaria interventions: a tool to support malaria strategic planning in Tanzania. PLoS ONE. 2020;15:e0228469.CrossRef Runge M, Snow RW, Molteni F, Thawer S, Mohamed A, Mandike R, et al. Simulating the council-specific impact of anti-malaria interventions: a tool to support malaria strategic planning in Tanzania. PLoS ONE. 2020;15:e0228469.CrossRef
13.
go back to reference Ye Y, Andrada A. Estimating malaria incidence through modeling is a good academic exercise, but how practical is it in high-burden settings? Am J Trop Med Hyg. 2020;102:701–2.CrossRef Ye Y, Andrada A. Estimating malaria incidence through modeling is a good academic exercise, but how practical is it in high-burden settings? Am J Trop Med Hyg. 2020;102:701–2.CrossRef
14.
go back to reference Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC) (Tanzania Mainland), Ministry of Health (MoH) (Zanzibar), National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS), and ICF. Tanzania Malaria Indicator Survey 2008. Dar es Salaam, Tanzania, and Rockville, USA. Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC) (Tanzania Mainland), Ministry of Health (MoH) (Zanzibar), National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS), and ICF. Tanzania Malaria Indicator Survey 2008. Dar es Salaam, Tanzania, and Rockville, USA.
15.
go back to reference Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC) (Tanzania Mainland), Ministry of Health (MoH) (Zanzibar), National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS), and ICF. Tanzania malaria indicator survey 2017. Dar es Salaam, Tanzania, Rockville, USA. Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC) (Tanzania Mainland), Ministry of Health (MoH) (Zanzibar), National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS), and ICF. Tanzania malaria indicator survey 2017. Dar es Salaam, Tanzania, Rockville, USA.
16.
go back to reference National Malaria Control Programme (NMCP), Tanzania. Mid-term review report of national malaria strategic plan 2015–2020. Ministry of Health, Community Development, Gender, Elderly and Children; Tanzania; 2017. National Malaria Control Programme (NMCP), Tanzania. Mid-term review report of national malaria strategic plan 2015–2020. Ministry of Health, Community Development, Gender, Elderly and Children; Tanzania; 2017.
17.
go back to reference National Malaria Control Programme (NMCP), Tanzania. Consultative malaria expert meeting report 2018. Ministry of Health, Community Development, Gender, Elderly and Children; Tanzania; 2018. National Malaria Control Programme (NMCP), Tanzania. Consultative malaria expert meeting report 2018. Ministry of Health, Community Development, Gender, Elderly and Children; Tanzania; 2018.
18.
go back to reference National Malaria Control Programme (NMCP), Tanzania. Supplementary midterm malaria strategic plan 2018–2020. Ministry of Health, Community Development, Gender, Elderly and Children; Tanzania; 2018. National Malaria Control Programme (NMCP), Tanzania. Supplementary midterm malaria strategic plan 2018–2020. Ministry of Health, Community Development, Gender, Elderly and Children; Tanzania; 2018.
19.
go back to reference Runge M, Molteni F, Mandike R, Snow RW, Lengeler C, Mohamed A, et al. Applied mathematical modelling to inform national malaria policies, strategies and operations in Tanzania. Malar J. 2020;19:101.CrossRef Runge M, Molteni F, Mandike R, Snow RW, Lengeler C, Mohamed A, et al. Applied mathematical modelling to inform national malaria policies, strategies and operations in Tanzania. Malar J. 2020;19:101.CrossRef
20.
go back to reference National Bureau of Statistics (Tanzania), Tanzania, Office of Chief Government Statistician (Zanzibar). Sub-Divisional population projections for year 2016 and 2017 based on 2012 population and housing census. Dar es Salaam; 2016. National Bureau of Statistics (Tanzania), Tanzania, Office of Chief Government Statistician (Zanzibar). Sub-Divisional population projections for year 2016 and 2017 based on 2012 population and housing census. Dar es Salaam; 2016.
21.
go back to reference Tanzania Local Government (Urban Authorities) Act; 1982. Tanzania Local Government (Urban Authorities) Act; 1982.
22.
go back to reference National Bureau of Statistics (Tanzania), Tanzania, Office of Chief Government Statistician (Zanzibar). 2012 Population and housing census. Dar es Salaam; 2013. National Bureau of Statistics (Tanzania), Tanzania, Office of Chief Government Statistician (Zanzibar). 2012 Population and housing census. Dar es Salaam; 2013.
23.
go back to reference WHO. Malaria surveillance, monitoring & evaluation: a reference manual. Geneva: World Health Organization; 2018. WHO. Malaria surveillance, monitoring & evaluation: a reference manual. Geneva: World Health Organization; 2018.
25.
go back to reference Brunner NC, Chacky F, Mandike R, Mohamed A, Runge M, Thawer SG, et al. The potential of pregnant women as a sentinel population for malaria surveillance. Malar J. 2019;18:370.CrossRef Brunner NC, Chacky F, Mandike R, Mohamed A, Runge M, Thawer SG, et al. The potential of pregnant women as a sentinel population for malaria surveillance. Malar J. 2019;18:370.CrossRef
26.
go back to reference Willilo RA, Molteni F, Mandike R, Mugalura FE, Mutafungwa A, Thadeo A, et al. Pregnant women and infants as sentinel populations to monitor prevalence of malaria: results of pilot study in Lake Zone of Tanzania. Malar J. 2016;15:392.CrossRef Willilo RA, Molteni F, Mandike R, Mugalura FE, Mutafungwa A, Thadeo A, et al. Pregnant women and infants as sentinel populations to monitor prevalence of malaria: results of pilot study in Lake Zone of Tanzania. Malar J. 2016;15:392.CrossRef
27.
go back to reference Kitojo C, Gutman JR, Chacky F, Kigadye E, Mkude S, Mandike R, et al. Estimating malaria burden among pregnant women using data from antenatal care centres in Tanzania: a population-based study. Lancet Global Health. 2019;7:e1695–705.CrossRef Kitojo C, Gutman JR, Chacky F, Kigadye E, Mkude S, Mandike R, et al. Estimating malaria burden among pregnant women using data from antenatal care centres in Tanzania: a population-based study. Lancet Global Health. 2019;7:e1695–705.CrossRef
29.
go back to reference Hay SI, Smith DL, Snow RW. Measuring malaria endemicity from intense to interrupted transmission. Lancet Infect Dis. 2008;8:369–78.CrossRef Hay SI, Smith DL, Snow RW. Measuring malaria endemicity from intense to interrupted transmission. Lancet Infect Dis. 2008;8:369–78.CrossRef
30.
go back to reference WHO. From malaria control to malaria elimination: a manual for elimination scenario planning. Geneva: World Health Organization, Global Malaria Programme; 2014. WHO. From malaria control to malaria elimination: a manual for elimination scenario planning. Geneva: World Health Organization, Global Malaria Programme; 2014.
31.
go back to reference Snow R, Marsh K. The consequences of reducing Plasmodium falciparum transmission in Africa. Adv Parasitol. 2002;52:235–64.CrossRef Snow R, Marsh K. The consequences of reducing Plasmodium falciparum transmission in Africa. Adv Parasitol. 2002;52:235–64.CrossRef
32.
go back to reference Snow RW. Sixty years trying to define the malaria burden in Africa: have we made any progress? BMC Med. 2014;12:227.CrossRef Snow RW. Sixty years trying to define the malaria burden in Africa: have we made any progress? BMC Med. 2014;12:227.CrossRef
33.
go back to reference Noor AM, Gething PW, Alegana VA, Patil AP, Hay SI, Muchiri E, et al. The risks of malaria infection in Kenya in 2009. BMC Infect Dis. 2009;9:180.CrossRef Noor AM, Gething PW, Alegana VA, Patil AP, Hay SI, Muchiri E, et al. The risks of malaria infection in Kenya in 2009. BMC Infect Dis. 2009;9:180.CrossRef
34.
go back to reference Tusting LS, Bousema T, Smith DL, Drakeley C. Measuring changes in Plasmodium falciparum transmission: precision, accuracy and costs of metrics. Adv Parasitol. 2014;84:151–208.CrossRef Tusting LS, Bousema T, Smith DL, Drakeley C. Measuring changes in Plasmodium falciparum transmission: precision, accuracy and costs of metrics. Adv Parasitol. 2014;84:151–208.CrossRef
35.
go back to reference Kigozi SP, Kigozi RN, Sserwanga A, Nankabirwa JI, Staedke SG, Kamya MR, et al. Malaria burden through routine reporting: relationship between incidence and test positivity rates. Am J Trop Med Hyg. 2019;101:137–47.CrossRef Kigozi SP, Kigozi RN, Sserwanga A, Nankabirwa JI, Staedke SG, Kamya MR, et al. Malaria burden through routine reporting: relationship between incidence and test positivity rates. Am J Trop Med Hyg. 2019;101:137–47.CrossRef
36.
go back to reference Omumbo JA, Noor AM, Fall IS, Snow RW. How well are malaria maps used to design and finance malaria control in Africa? PLoS ONE. 2013;8:e53198.CrossRef Omumbo JA, Noor AM, Fall IS, Snow RW. How well are malaria maps used to design and finance malaria control in Africa? PLoS ONE. 2013;8:e53198.CrossRef
37.
go back to reference Mayor A, Menéndez C, Walker PGT. Targeting pregnant women for malaria surveillance. Trends Parasitol. 2019;35:677–86.CrossRef Mayor A, Menéndez C, Walker PGT. Targeting pregnant women for malaria surveillance. Trends Parasitol. 2019;35:677–86.CrossRef
38.
go back to reference van Eijk AM, Hill J, Noor AM, Snow RW, ter Kuile FO. Prevalence of malaria infection in pregnant women compared with children for tracking malaria transmission in sub-Saharan Africa: a systematic review and meta-analysis. Lancet Glob Health. 2015;3:e617–28.CrossRef van Eijk AM, Hill J, Noor AM, Snow RW, ter Kuile FO. Prevalence of malaria infection in pregnant women compared with children for tracking malaria transmission in sub-Saharan Africa: a systematic review and meta-analysis. Lancet Glob Health. 2015;3:e617–28.CrossRef
39.
go back to reference Metselaar D, Van Thiel PH. Classification of malaria. Trop Geogr Med. 1959;11:157–61. Metselaar D, Van Thiel PH. Classification of malaria. Trop Geogr Med. 1959;11:157–61.
40.
go back to reference Brooker S, Kolaczinski JH, Gitonga CW, Noor AM, Snow RW. The use of schools for malaria surveillance and programme evaluation in Africa. Malar J. 2009;8:231.CrossRef Brooker S, Kolaczinski JH, Gitonga CW, Noor AM, Snow RW. The use of schools for malaria surveillance and programme evaluation in Africa. Malar J. 2009;8:231.CrossRef
41.
go back to reference Nankabirwa J, Wandera B, Kiwanuka N, Staedke SG, Kamya MR, Brooker SJ. Asymptomatic Plasmodium infection and cognition among primary schoolchildren in a high malaria transmission setting in Uganda. Am J Trop Med Hyg. 2013;88:1102–8.CrossRef Nankabirwa J, Wandera B, Kiwanuka N, Staedke SG, Kamya MR, Brooker SJ. Asymptomatic Plasmodium infection and cognition among primary schoolchildren in a high malaria transmission setting in Uganda. Am J Trop Med Hyg. 2013;88:1102–8.CrossRef
42.
go back to reference Snow RW & Noor AM (2015). Malaria risk mapping in Africa: The historical context to the Information for Malaria (INFORM) project. Working Paper in support of the INFORM Project funded by the Department for International Development and the Wellcome Trust, Nairobi, Kenya, 2015. Snow RW & Noor AM (2015). Malaria risk mapping in Africa: The historical context to the Information for Malaria (INFORM) project. Working Paper in support of the INFORM Project funded by the Department for International Development and the Wellcome Trust, Nairobi, Kenya, 2015.
43.
go back to reference Giorgi E, Diggle PJ, Snow RW, Noor AM. Geostatistical methods for disease mapping and visualization using data from spatio-temporally referenced prevalence surveys. Int Stat Rev. 2018;arXiv:1802.06359. Giorgi E, Diggle PJ, Snow RW, Noor AM. Geostatistical methods for disease mapping and visualization using data from spatio-temporally referenced prevalence surveys. Int Stat Rev. 2018;arXiv:​1802.​06359.
44.
go back to reference Bhattacharya AA, Umar N, Audu A, Felix H, Allen E, Schellenberg JRM, et al. Quality of routine facility data for monitoring priority maternal and newborn indicators in DHIS2: a case study from Gombe State, Nigeria. PLoS ONE. 2019;14:e0211265.CrossRef Bhattacharya AA, Umar N, Audu A, Felix H, Allen E, Schellenberg JRM, et al. Quality of routine facility data for monitoring priority maternal and newborn indicators in DHIS2: a case study from Gombe State, Nigeria. PLoS ONE. 2019;14:e0211265.CrossRef
45.
go back to reference Rowe AK, Kachur SP, Yoon SS, Lynch M, Slutsker L, Steketee RW. Caution is required when using health facility-based data to evaluate the health impact of malaria control efforts in Africa. Malar J. 2009;8:209.CrossRef Rowe AK, Kachur SP, Yoon SS, Lynch M, Slutsker L, Steketee RW. Caution is required when using health facility-based data to evaluate the health impact of malaria control efforts in Africa. Malar J. 2009;8:209.CrossRef
46.
go back to reference Ashton RA, Bennett A, Al-Mafazy A-W, Abass AK, Msellem MI, McElroy P, et al. Use of routine health information system data to evaluate impact of malaria control interventions in Zanzibar, Tanzania from 2000 to 2015. EClinicalMedicine. 2019;12:11–9.CrossRef Ashton RA, Bennett A, Al-Mafazy A-W, Abass AK, Msellem MI, McElroy P, et al. Use of routine health information system data to evaluate impact of malaria control interventions in Zanzibar, Tanzania from 2000 to 2015. EClinicalMedicine. 2019;12:11–9.CrossRef
47.
go back to reference Ashton RA, Bennett A, Yukich J, Bhattarai A, Keating J, Eisele TP. Methodological considerations for use of routine health information system data to evaluate malaria program impact in an era of declining malaria transmission. Am J Trop Med Hyg. 2017;97(3 Suppl):46–57.CrossRef Ashton RA, Bennett A, Yukich J, Bhattarai A, Keating J, Eisele TP. Methodological considerations for use of routine health information system data to evaluate malaria program impact in an era of declining malaria transmission. Am J Trop Med Hyg. 2017;97(3 Suppl):46–57.CrossRef
48.
go back to reference Bennett A, Yukich J, Miller JM, Vounatsou P, Hamainza B, Ingwe MM, et al. A methodological framework for the improved use of routine health system data to evaluate national malaria control programs: evidence from Zambia. Popul Health Metrics. 2014;12:30.CrossRef Bennett A, Yukich J, Miller JM, Vounatsou P, Hamainza B, Ingwe MM, et al. A methodological framework for the improved use of routine health system data to evaluate national malaria control programs: evidence from Zambia. Popul Health Metrics. 2014;12:30.CrossRef
49.
go back to reference Alegana VA, Wright JA, Pentrina U, Noor AM, Snow RW, Atkinson PM. Spatial modelling of healthcare utilisation for treatment of fever in Namibia. Int J Health Geogr. 2012;11:6.CrossRef Alegana VA, Wright JA, Pentrina U, Noor AM, Snow RW, Atkinson PM. Spatial modelling of healthcare utilisation for treatment of fever in Namibia. Int J Health Geogr. 2012;11:6.CrossRef
50.
go back to reference Cibulskis RE, Aregawi M, Williams R, Otten M, Dye C. Worldwide incidence of malaria in 2009: estimates, time trends, and a critique of methods. PLoS Med. 2011;8:e1001142.CrossRef Cibulskis RE, Aregawi M, Williams R, Otten M, Dye C. Worldwide incidence of malaria in 2009: estimates, time trends, and a critique of methods. PLoS Med. 2011;8:e1001142.CrossRef
51.
go back to reference Alegana VA, Atkinson PM, Lourenço C, Ruktanonchai NW, Bosco C, Erbach-Schoenberg EZ, et al. Advances in mapping malaria for elimination: fine resolution modelling of Plasmodium falciparum incidence. Sci Rep. 2016;6:29628.CrossRef Alegana VA, Atkinson PM, Lourenço C, Ruktanonchai NW, Bosco C, Erbach-Schoenberg EZ, et al. Advances in mapping malaria for elimination: fine resolution modelling of Plasmodium falciparum incidence. Sci Rep. 2016;6:29628.CrossRef
52.
go back to reference Thwing J, Camara A, Candrinho B, Zulliger R, Colborn J, Painter J, et al. A robust estimator of malaria incidence from routine health facility data. Am J Trop Med Hyg. 2019;102:811–20.CrossRef Thwing J, Camara A, Candrinho B, Zulliger R, Colborn J, Painter J, et al. A robust estimator of malaria incidence from routine health facility data. Am J Trop Med Hyg. 2019;102:811–20.CrossRef
Metadata
Title
Sub-national stratification of malaria risk in mainland Tanzania: a simplified assembly of survey and routine data
Authors
Sumaiyya G. Thawer
Frank Chacky
Manuela Runge
Erik Reaves
Renata Mandike
Samwel Lazaro
Sigsbert Mkude
Susan F. Rumisha
Claud Kumalija
Christian Lengeler
Ally Mohamed
Emilie Pothin
Robert W. Snow
Fabrizio Molteni
Publication date
01-12-2020
Publisher
BioMed Central
Keyword
Malaria
Published in
Malaria Journal / Issue 1/2020
Electronic ISSN: 1475-2875
DOI
https://doi.org/10.1186/s12936-020-03250-4

Other articles of this Issue 1/2020

Malaria Journal 1/2020 Go to the issue