The epidemiology of residual Plasmodium falciparum malaria transmission and infection burden in an African city with high coverage of multiple vector control measures

Abstract

Background: In the Tanzanian city of Dar es Salaam, high coverage of long-lasting insecticidal nets (LLINs), larvicide application (LA) and mosquito-proofed housing, was complemented with improved access to artemisinin-based combination therapy and rapid diagnostic tests by the end of 2012.

Methods: Three rounds of city-wide, cluster-sampled cross-sectional surveys of malaria parasite infection status, spanning 2010 to 2012, were complemented by two series of high-resolution, longitudinal surveys of vector density.

Results: Larvicide application using a granule formulation of Bacillus thuringiensis var. israelensis (Bti) had no effect upon either vector density (P = 0.820) or infection prevalence (P = 0.325) when managed by a private-sector contractor. Infection prevalence rebounded back to 13.8 % in 2010, compared with <2 % at the end of a previous Bti LA evaluation in 2008. Following transition to management by the Ministry of Health and Social Welfare (MoHSW), LA consistently reduced vector densities, first using the same Bti granule in early 2011 [odds ratio (OR) (95 % confidence interval (CI)) = 0.31 (0.14, 0.71), P = 0.0053] and then a pre-diluted aqueous suspension formulation from mid 2011 onwards [OR (95 % CI) = 0.15 (0.07, 0.30), P ≪ 0.000001]. While LA by MoHSW with the granule formulation was associated with reduced infection prevalence [OR (95 % CI) = 0.26 (0.12, 0.56), P = 0.00040], subsequent liquid suspension use, following a mass distribution to achieve universal coverage of LLINs that reduced vector density [OR (95 % CI) = 0.72 (0.51, 1.01), P = 0.057] and prevalence [OR (95 % CI) = 0.80 (0.69, 0.91), P = 0.0013], was not associated with further prevalence reduction (P = 0.836). Sleeping inside houses with complete window screens only reduced infection risk [OR (95 % CI) = 0.71 (0.62, 0.82), P = 0.0000036] if the evenings and mornings were also spent indoors. Furthermore, infection risk was only associated with local vector density [OR (95 % CI) = 6.99 (1.12, 43.7) at one vector mosquito per trap per night, P = 0.037] among the minority (14 %) of households lacking screening. Despite attenuation of malaria transmission and immunity, 88 % of infected residents experienced no recent fever, only 0.4 % of these afebrile cases had been treated for malaria, and prevalence remained high (9.9 %) at the end of the study.

Conclusions: While existing vector control interventions have dramatically attenuated malaria transmission in Dar es Salaam, further scale-up and additional measures to protect against mosquito bites outdoors are desirable. Accelerated elimination of chronic human infections persisting at high prevalence will require active, population-wide campaigns with curative drugs.

Keywords: Anopheles; Chronic infection; Housing; Larval source management; Long-lasting insecticidal net; Malaria; Mosquito; Plasmodium; Vector control; Window screening.

Fig. 1

Map of where Dar es Salaam city region is located within Tanzania (a), the study area within the city and its three municipalities (b), and the survey locations and wards in which larvicides were applied (c)

Fig. 2

Long-term trends in coverage with malaria control interventions, entomological malaria transmission hazard, and prevalence of fever and malaria infection. To allow direct comparison of results from this study from 2010 to 2012, with the previous study from 2004 to 2008 [15, 40], only data from the original 15 city centre wards common to both studies (Fig. 1) were included and summarized by survey round. a Schematic summary of specific intervention introductions; b Stayed in a ward with larvicide application (LA) last night; c Stayed in a house with mosquito-proofed windows, ceilings or eaves; d Used a bed net or long-lasting insecticidal nets (LLIN) the previous night; e Treated with an artemisinin-based therapy, including artemisinin-based combination therapy (ACT), or with any other anti-malarial, if had a fever in the previous 2 weeks; f Outdoor rates of human exposure to biting malaria vectors; g Outdoor rates of human exposure to infectious bites by malaria vectors; h Prevalence of reported fever and parasitologically-confirmed malaria infection

Fig. 3

Short-term trends in coverage with malaria control interventions across the city of Dar es Salaam over the course of this study, summarized by quarterly mean. a Schematic summary of specific intervention introductions; b Vector densities; c Prevalence of Plasmodium falciparum infection and recollection of fever; d Anti-malarial drug use; e Bed net use the previous night; f Stayed in a mosquito-proofed house; g Proportion of potential human exposure to biting vectors expected to occur while asleep or indoors in the absence of protective bed nets or mosquito-proofed housing; h Stayed in a ward with larvicide application (LA) last night

Fig. 4

Time trends in physiological susceptibility to pyrethroids (a), sibling species composition (b), and biting activity distribution (c) of Anopheles gambiae sensu lato in Dar es Salaam. Physiological susceptibility estimates (a) were obtained from published surveys [110]. Sibling species composition data (b) were obtained from PCR analysis of mosquitoes caught through both the routine surveillance collections described here and a range of published [9, 10, 66, 68] and unpublished experimental studies of trapping methods conducted at intense sampling in foci of high vector density. Biting activity distribution data (c) were obtained from outdoor HLC data obtained through either routine surveillance from 2005 to 2008, or through quality assurance surveys of routine CB mosquito trapping with Ifakara tent traps between 2011 and 2012

Fig. 5

The geographic distribution of surveyed locations with detectable populations of Anopheles gambiae vectors (a, c, e) and > 10 % Plasmodium falciparum infection prevalence (b, d, f) over the periods from March to December 2010 when application of a granular formulation of Bacillus thuriniensis var. israelensis (Bti) in the wards highlighted in green was managed by a private sector contractor (a, b), from January to August 2011 when the same granular formulation was applied under management of the Ministry of Health and Social Welfare (MoHSW) in the same wards highlighted in green (c, d), and from September 2011 onwards when a pre-diluted liquid formulation of Bti was applied under MoHSW management in the wards highlighted in green and yellow (e, f)

Fig. 6

The frequency distribution and dependence of Plasmodium falciparum malaria prevalence upon densities of Anopheles gambiae sensu lato in Dar es Salaam. The number and proportion (a, b) of RDT-tested human subjects, as well as the proportion of those which were diagnosed as infected with malaria in houses with (e, f) and without (c, d) window screening, are plotted against vector density, as measured by community based surveillance with Ifakara tent traps (a, c, e) and converted into the estimated equivalent outdoor human landing catch (b, d, f). Continuous lines represent the best fit of models relating malaria infection prevalence to vector density in houses with (c, d) and without (e, f) window screens

Fig. 7

Age-prevalence profiles for Plasmodium falciparum malaria infection observed by microscopy in previous cross-sectional surveys from 2004 to 2008 [15] (a) and by rapid diagnostic test in surveys during these subsequent surveys between 2010 and 2012 (b)

Fig. 8

Times at which individuals interviewed during cross-sectional household surveys in Dar es Salaam reported having gone indoors for the evening, gone to bed for the evening, gotten out of bed in the morning and left the house in the morning, the previous night, stratified by derived individual estimates for the proportion of exposure to An. gambiae bites that would occur indoors in the absence of a bed net or window screening (π _i). For comparison with the biting activity profile of the most important malaria vector in the city, these frequencies of human behaviours are plotted alongside the human biting rates measured by human landing catch (HLC) in selected areas of relatively high vector density in 2006 [9, 10] that were used to calculate these individual estimates for π _i