Introduction

Lymphatic filariasis (LF) is a Neglected Tropical Disease (NTD) endemic in 73 tropical and sub-tropical countries [1]. It is caused by three species of filarial worms – Wuchereria bancrofti, Brugia malayi and Brugia timori – and is transmitted by multiple species of mosquitoes. The disease manifests as a spectrum of clinical conditions, the most prominent being hydrocele, chronic lymphoedema/elephantiasis of legs and arms, and sub-clinical lymphatic damage, even in young children. Affected individuals suffer from disability, stigma and associated social and economic hardship. Marginalized populations, particularly those living in areas with inadequate sanitation and sub-standard housing conditions are particularly vulnerable and thus most likely to be affected by the disease. According to the initial estimates compiled in 1996, 1.2 billion people were living in areas where they were ‘at-risk’ of acquiring LF and 120 million people were infected, 40 million of whom experienced one or more chronic disease manifestations [2].

In 1997, the World Health Assembly, through resolution 50.29 (WHA 50.29), urged member states and the WHO to capitalize on both new advances in the understanding of lymphatic filariasis and the opportunities for its elimination by developing national plans of action that would lead to the eventual elimination of the disease as a public health problem. In principal, the elimination strategy is relatively straightforward, involving a pre-implementation phase of epidemiological assessment (‘mapping’) followed by a minimum of five annual cycles of once-yearly mass preventive chemotherapy (mass drug administration [MDA]) to all eligible populations residing in geographic zones determined to be endemic. Each cycle of preventive chemotherapy employs a ‘single-dose’ co-administration of two anthelmintics that have impact on adult parasites but are especially effective at reducing microfilariae, the transmission stage of filarial parasites circulating in the blood, to very low levels for periods up to 12 months or more, thereby inhibiting transmission of the microfilaria to mosquitoes. By depleting the reservoir of infectious stages of the parasite across broad geographic areas for five years or more, the transmission cycle of the parasite is expected to be interrupted for long enough to significantly influence parasite population dynamics to the point where elimination is possible [3].

Utilizing a rapid diagnostic test that permits detection of adult filarial worm antigen in daytime blood, national programs first determined the geographic distribution of infection and then embarked on LF elimination [3]. Through early epidemiological assessments and modeling, the initial size of the global population requiring intervention was estimated; the 2013 revised estimate by WHO for the total population living in areas where filariasis had been endemic when the GPELF began in 2000 (i.e., were ‘at risk’ of infection and, thus, required preventive chemotherapy for lymphatic filariasis) was 1.4 billion [1], [2]. Since the beginning of the program in 2000 through the end of 2012, however, 4.4 billion doses of anthelmintics had been administered to populations in 56 of the endemic countries, so it is clear that the number of at-risk individuals will have changed [1]. Indeed, the following analysis was conducted to estimate the impact that this global campaign (the Global Programme to Eliminate Lymphatic Filariasis [GPELF]), after its first 13 years, has had on the number of people living at risk of LF infection.

Methods

The Model

The population remaining at-risk of infection following a series of MDAs can be modeled for each LF-endemic country using the following general algorithm:where:

A =  Population still at-risk of infection

B =  Initial population at risk at baseline

T_n =  Population treated at n^th round of MDA

t_max =  Maximum population treated in any round prior to t_n

n =  Total number of MDAs

Since data at the implementation Unit (IU) level is not available in the PCT Databank for each country, the model builds ‘bottom-up’ from the sub-national to the national level, predicated on the number of new persons treated each year (i.e., the treatment cohorts) and followed over time. This approach permits the model to handle staggered MDA rounds on a sub-national level by assigning each cohort its appropriate rate of ‘at-risk’ decline based on the specific number of MDAs it has experienced, rather than applying an average round of treatments for the whole country (see Fig. 1).

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Figure 1. Depiction of progressive scale-up of a national program to full geographic coverage over 3 years.

This figure demonstrates the heterogeneous levels of infection risk depending on the number of MDAs experienced by different cohorts of the population defined by when they first received MDA.

https://doi.org/10.1371/journal.pntd.0003333.g001

The model comprises three temporal components:

1. Before MDA (A = B): This part of the model simply states that population still at-risk of infection and requiring treatment is equal to the initial at-risk population at baseline as defined by the WHO PCT Databank (see Assumption 1 below).
2. During years 1–4 of MDA (B – 0.5[t_n-t_max]….0.94[t_n-t_max]): The function [t_n-t_max] equals the number of new (i.e., unique) individuals treated in a particular year where t_n is the total number treated in the year and t_max is the maximum population treated in any prior year (see Assumption 2 below). Therefore, in the initial MDA for any IU, [t_n-t_max] equals t₁ because there is only one MDA and no previous treatment (i.e., t_max  = 0). Following this first round of MDA, the model presumes that the baseline population at risk of infection is reduced by 50% of the treated population (i.e., 0.5[t₁]). From MDAs 2–4, the population of this initial treated cohort t₁ remains the same but the discount factor (‘decreased transmission’) increases to 75% after the second MDA, 88% after the third MDA, and 94% after the fourth MDA.

Meanwhile, the same IU or additional IUs may be scaling up treatment in subsequent years. Again, the model determines only the new population treated in each MDA as [t_n-t_max] where t_n is the total population treated in the following year and t_max is the maximum total population treated in any previous year (t_max ≠ 0 after the first year). Each group of [t_n-t_max] can now be clearly seen in the model as a mutually exclusive cohort (summed to the national level) based on the number of MDA treatments it has received. This avoids double counting of populations while enforcing proper assignment of infection reduction rates to each treated cohort; the newest ones are closer to the left side of the equation and receive the smallest percent reduction. The model also accounts both for years without new MDA cohorts and for MDAs skipped altogether (see Assumptions 3–5 below).

1. Year 5 and after of MDA (Σ…): The model presumes that any population cohort treated with five or more annual MDAs will see its population at-risk reduced by 100% of its pre-treatment level. As a result, the entire sum of these cohorts can be subtracted from the baseline population at risk of infection. The model, however, only reduces the entire at-risk population to zero following programmatic completion of an appropriate evaluation survey (see Figure 1 and Assumption 6 below).

Results

Estimated Global Achievements (through 2012)

Aggregating the country populations requiring MDA for LF upon completion of mapping (as described above) yields a global total baseline of approximately 1.46 billion people at risk of infection. Applying the model and its assumptions to data from each individual country (schematized in Figure 1) yielded the progressive decline in the at-risk population seen in Figure 2. After 13 years of LF MDA, the global total of 1.46 billion people requiring treatment is estimated to have decreased by 46% to 789 million through 2012.

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Figure 2. Global decline of population at-risk for lymphatic filariasis.

Thirteen years of mass drug administration for lymphatic filariasis have resulted in a 46% decline in the population at risk to 789 million by 2012.

https://doi.org/10.1371/journal.pntd.0003333.g002

Estimated Regional Achievements (Figure 3)

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Figure 3. Progressive decline in population at-risk for lymphatic filariasis, by region.

Regions have achieved differing levels of progress in reducing the population at risk of lymphatic filariasis.

https://doi.org/10.1371/journal.pntd.0003333.g003

Southeast Asia Region (SEAR).

In SEAR, where the highest burden globally of lymphatic filariasis is found, wide-reaching treatment programs have led to a 57% decrease in the number of people at-risk for LF from an initial at-risk population of over 900 million in 1999 to just over 390 million by the end of 2012. The majority of those still at-risk in this region (over 75% in 2012) are found in India (which has already achieved a decline of nearly 70% through 2012) and Indonesia, which is just now rapidly scaling up its elimination program.

Africa Region (AFR).

The African region – with the second highest LF burden globally – still has nearly 350 million people at-risk, a decline of approximately 25% since 2000. The reasons for its relatively slow progress include the inability to treat in Loa loa co-endemic areas located in tropical Central Africa, local conflict, and, especially, inadequate financial resources. The highest burden countries in this region – Nigeria, the Democratic Republic of Congo, and Tanzania – represent 50% of the remaining population living in areas at-risk for LF in AFR (as of 2012).

Eastern Mediterranean Region (EMR).

Two of the 4 endemic countries in this region – Egypt and Yemen – have completed or almost completed the MDA phase of their LF programs. (Note that as of 2012, South Sudan was still part of the Eastern Mediterranean Region; it moved to the Africa Region in 2013.) Sudan is the highest-burden country in this region (with 92% of the EMR population remaining at risk), and has experienced considerable delays in program roll-out because of recurrent civil unrest.

Western Pacific Region (WPR).

Nine WPR countries are currently in a post-MDA surveillance phase of their LF programs, following successful treatment campaigns and reaching the WHO program end-points as determined by a transmission assessment survey. The majority of the remaining burden lies in the Philippines and Papua New Guinea. The Philippines, with 72% of the remaining population at risk in the region, has achieved a 55% decrease in at-risk individuals, but Papua New Guinea currently accounts for 24% of the regional population requiring LF MDA and is yet to achieve scale-up to full geographic coverage.

Americas (AMR).

The smallest regional population requiring LF MDA is found in the AMR – just over 4 million people living principally in Haiti, Brazil, and Guyana. By the end of 2012, the region achieved a 62% decline in individuals at-risk of LF infection.

Discussion

During its first 13 years, WHO's Global Programme to Eliminate Lymphatic Filariasis achieved enormous progress by distributing 4.4 billion treatments in 56 countries and achieving (from our calculations) an estimated 46% reduction in the population at risk of LF from 1.46 billion to 789 million people. By the end of 2012, 13 countries had entered the post-MDA surveillance phase. The available data show that all regions have made substantial progress towards achieving the elimination target of 2020, and for most regions the preponderance of what is left to be achieved is restricted to a few countries with large populations. Overall, these impressive accomplishments were possible only because of strong global partnerships and the commitment of national governments in collaboration with pharmaceutical company partners donating billions of tablets of medicine (Mectizan by Merck & Co., Inc.; albendazole by GlaxoSmithKline; diethylcarbamazine [DEC] by Eisai), bilateral and other donors, non-governmental organizations and researchers, all with guidance and leadership from the World Health Organization. Estimating the number of people freed from the risk of infection is important for all of these key constituencies in order to define the progress being made, while also calling attention to the need to speed the expansion of intervention efforts to ensure that the global elimination targets can be reached.

The accuracy of the estimates from the present model, however, depends on the appropriateness of its underlying assumptions. There is potential both for overestimating the effect of the GPELF in decreasing the number of people at-risk of LF infection and for underestimating it.

A major limitation of this model is its total reliance on the WHO PCT Databank for information on the numbers of people treated each year in the Global Programme. The data is self-reported by national programs, and while in most situations where it has been examined the reported coverage and the independently-surveyed coverage have been similar, there are areas where frequent over-reporting has been identified (reviewed in [18]). Such over-reported coverage would lead the model to overestimate the reduction in at-risk population by the GPELF. On the other hand, for the program to be effective, LF MDA guidelines recommend treating at least 65% of the total population in each targeted implementation unit, recognizing that the untreated percentage of the population still garners some level of protection from the treatments in their communities [19]. Since our current model is based on actual treatments distributed, its estimates do not include this additional ‘herd protection’ in populations covered by MDA and, thus could be underestimating overall Programme effects in decreasing the number of at-risk individuals.

Also leading the model potentially to underestimate the decrease in numbers of at-risk individuals is the technical convention that the model uses in not ‘zeroing out’ an at-risk population until all districts in the country have programmatically passed a Transmission Assessment Survey (TAS) or equivalent. The remaining population at-risk in a country with more than 5 rounds of MDA is likely, therefore, to be overestimated by the model, and the model will show sharp drops in the estimated at-risk population over the next several years as more countries implement the TAS, stop mass treatment, and enter a post-treatment surveillance phase.

The model used in this study also has important additional limitations related to its initial assumptions.

1. It is a ‘vector-based model.’ The model relies on vector infectivity data post-MDA to estimate LF transmission decrease in human populations using a curve developed earlier and reflected in the integer values of the model's formula [15], [16]. Though data from all three mosquito genera transmitting LF were used to generate the model parameters, the biology of LF infections clearly reflects the characteristics of the vectors, and these differences (whether leading to overestimates or underestimates) are not accounted for currently. Further, extensive advances in vector control interventions in the past decade – particularly in Africa – including the distribution and usage of bed nets, may provide an added benefit of reduced LF transmission; this impact is not currently captured in the model.
2. Re-infection. The model does not take into account the possibility of re-infection or resurgence of suppressed infections in areas that miss rounds of treatment, in areas with rounds treating fewer individuals than previous rounds, and in areas achieving consistently poor drug coverage. It is unknown to what extent there could be some level of infection increase in these populations such that they would become an increased risk of infection to others. Since the mosquito infectivity depends on the microfilaremia prevalence in humans, and since the kinetics of the changes in mosquito and human infections post-treatment are not well-defined, it is unclear what interval between successive MDAs in a 5–6 year LF elimination program would lead to increased LF transmission and consequent increased risk of infection to the population.

Despite these modeling constraints, assessing progress of the Global Programme is essential both for demonstrating the successes already achieved and for identifying the challenges remaining. Viewed from the perspective of understanding the population at risk of LF globally, this model has estimated a 46% decrease in those still at risk of acquiring LF infection after 13 years of the GPELF. Clearly, this implies much progress to be celebrated, especially since, for the reasons described above, the ‘true’ reduction in at-risk individuals is likely to be even greater. It is also clear, however, that much more needs to be done – particularly in two important domains. The first is in optimizing MDA drug uptake rates (‘coverage’) in programs already underway, and the second is in extending current programs to those endemic countries (or regions within countries) not already engaged in LF elimination. Where programs have been established, results have been remarkable, but it will be necessary now to maximize program coverage, both programmatically and geographically, in order to meet the global goal of achieving elimination of LF as a public health problem by 2020.