Applied mathematical modelling to inform national malaria policies, strategies and operations in Tanzania

Runge, Manuela; Molteni, Fabrizio; Mandike, Renata; Snow, Robert W.; Lengeler, Christian; Amara, Mohamed; Pothin, Emilie

doi:10.1186/s12936-020-03173-0

Cited by 19 publications

(21 citation statements)

References 46 publications

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“…For sites pre-2010, similar, published geostatistical modelled approaches were used to obtain predicted Pf PR 2–10 but these models did not include covariate priors nor correct RDT to microscopy in Kenya [ 65 ] and Tanzania [ 66 ]. We have elected to use categorical definitions of parasite prevalence used by national malaria programmes in East Africa to select interventions most likely to provide optimised, efficient use of malaria prevention strategies sub-nationally [ 65 , 66 , 68 , 69 ]: low transmission intensity settings for Pf PR 2–10 < 5%, low-moderate for Pf PR 2–10 5–9%, moderate for Pf PR 2–10 10–29%, and high for Pf PR 2–10 ≥ 30%.…”

Section: Methodsmentioning

confidence: 99%

Malaria hospitalisation in East Africa: age, phenotype and transmission intensity

Kamau

Paton

Akech

et al. 2022

BMC Med

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Background Understanding the age patterns of disease is necessary to target interventions to maximise cost-effective impact. New malaria chemoprevention and vaccine initiatives target young children attending routine immunisation services. Here we explore the relationships between age and severity of malaria hospitalisation versus malaria transmission intensity. Methods Clinical data from 21 surveillance hospitals in East Africa were reviewed. Malaria admissions aged 1 month to 14 years from discrete administrative areas since 2006 were identified. Each site-time period was matched to a model estimated community-based age-corrected parasite prevalence to provide predictions of prevalence in childhood (PfPR2–10). Admission with all-cause malaria, severe malaria anaemia (SMA), respiratory distress (RD) and cerebral malaria (CM) were analysed as means and predicted probabilities from Bayesian generalised mixed models. Results 52,684 malaria admissions aged 1 month to 14 years were described at 21 hospitals from 49 site-time locations where PfPR2–10 varied from < 1 to 48.7%. Twelve site-time periods were described as low transmission (PfPR2–10 < 5%), five low-moderate transmission (PfPR2–10 5–9%), 20 moderate transmission (PfPR2–10 10–29%) and 12 high transmission (PfPR2–10 ≥ 30%). The majority of malaria admissions were below 5 years of age (69–85%) and rare among children aged 10–14 years (0.7–5.4%) across all transmission settings. The mean age of all-cause malaria hospitalisation was 49.5 months (95% CI 45.1, 55.4) under low transmission compared with 34.1 months (95% CI 30.4, 38.3) at high transmission, with similar trends for each severe malaria phenotype. CM presented among older children at a mean of 48.7 months compared with 39.0 months and 33.7 months for SMA and RD, respectively. In moderate and high transmission settings, 34% and 42% of the children were aged between 2 and 23 months and so within the age range targeted by chemoprevention or vaccines. Conclusions Targeting chemoprevention or vaccination programmes to areas where community-based parasite prevalence is ≥10% is likely to match the age ranges covered by interventions (e.g. intermittent presumptive treatment in infancy to children aged 2–23 months and current vaccine age eligibility and duration of efficacy) and the age ranges of highest disease burden.

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Section: Methodsmentioning

confidence: 99%

Malaria hospitalisation in East Africa: age, phenotype and transmission intensity

Kamau

Paton

Akech

et al. 2022

BMC Med

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“…This paper presents the first documentation of a national effort to combine multiple epidemiological indicators from different data sources to form a composite risk stratification. The process of policy development [19] and the allocation of interventions [18] following development of this malaria risk stratification are presented elsewhere.…”

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confidence: 99%

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

Thawer

Chacky

Runge

et al. 2020

Malar J

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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 (PfPR 5to16) were obtained from the two latest biennial council representative school malaria parasitaemia surveys, 2014-2015 and 2017. The PfPR 5to16 served as a guide to set appropriate cutoffs 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%PfPR 5to16), low (1− < 5%PfPR 5to16), moderate (5− < 30%PfPR 5to16) and high (≥ 30%PfPR 5to16). 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 northeast to southwest parts of the country, whilst the areas in the moderate to high strata were situated in the northwest and southeast 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.

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“…Stakeholders preferred to develop maps using data and processes that were owned, understood and trusted by the country. As noted in previous studies [22,46,48], the alignment with other sources of information and stakeholder expectations were considered important for stakeholders to have trust in the maps.…”

Section: Trust and Ownershipmentioning

confidence: 89%

How useful are malaria risk maps at the country level? Perceptions of decision-makers in Kenya, Malawi and the Democratic Republic of Congo

Ghilardi

Okello

Nyondo-Mipando

et al. 2020

Malar J

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Background Declining malaria prevalence and pressure on external funding have increased the need for efficiency in malaria control in sub-Saharan Africa (SSA). Modelled Plasmodium falciparum parasite rate (PfPR) maps are increasingly becoming available and provide information on the epidemiological situation of countries. However, how these maps are understood or used for national malaria planning is rarely explored. In this study, the practices and perceptions of national decision-makers on the utility of malaria risk maps, showing prevalence of parasitaemia or incidence of illness, was investigated. Methods A document review of recent National Malaria Strategic Plans was combined with 64 in-depth interviews with stakeholders in Kenya, Malawi and the Democratic Republic of Congo (DRC). The document review focused on the type of epidemiological maps included and their use in prioritising and targeting interventions. Interviews (14 Kenya, 17 Malawi, 27 DRC, 6 global level) explored drivers of stakeholder perceptions of the utility, value and limitations of malaria risk maps. Results Three different types of maps were used to show malaria epidemiological strata: malaria prevalence using a PfPR modelled map (Kenya); malaria incidence using routine health system data (Malawi); and malaria prevalence using data from the most recent Demographic and Health Survey (DRC). In Kenya the map was used to target preventative interventions, including long-lasting insecticide-treated nets (LLINs) and intermittent preventive treatment in pregnancy (IPTp), whilst in Malawi and DRC the maps were used to target in-door residual spraying (IRS) and LLINs distributions in schools. Maps were also used for operational planning, supply quantification, financial justification and advocacy. Findings from the interviews suggested that decision-makers lacked trust in the modelled PfPR maps when based on only a few empirical data points (Malawi and DRC). Conclusions Maps were generally used to identify areas with high prevalence in order to implement specific interventions. Despite the availability of national level modelled PfPR maps in all three countries, they were only used in one country. Perceived utility of malaria risk maps was associated with the epidemiological structure of the country and use was driven by perceived need, understanding (quality and relevance), ownership and trust in the data used to develop the maps.

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Applied mathematical modelling to inform national malaria policies, strategies and operations in Tanzania

Cited by 19 publications

References 46 publications

Malaria hospitalisation in East Africa: age, phenotype and transmission intensity

Malaria hospitalisation in East Africa: age, phenotype and transmission intensity

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

How useful are malaria risk maps at the country level? Perceptions of decision-makers in Kenya, Malawi and the Democratic Republic of Congo

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